CN103238041B - wide area positioning system - Google Patents

Abstract

Alignment system and method include the network of transmitter, and transmitter broadcasts the positioning signal for including distance measuring signal and positioning system information.Distance measuring signal includes being used for measuring the information of the distance of the transmitter of broadcast distance measuring signal.Reference sensor array including at least one reference sensor unit is located at known location.Remote receiver includes atmospheric sensor, and atmospheric sensor collects the atmosphere data of the opening position of remote receiver.Positioning application is couple to remote receiver, and uses air and the reference data from reference sensor array, generates the reference pressure estimate of the opening position of remote receiver.Positioning calculates the position of remote receiver, satellite-signal is the signal of satellite-based alignment system using reference pressure estimate and from least one information derived in positioning signal and satellite-signal.Position includes height above sea level.

Description

Wide area positioning system

RELATED APPLICATIONS

This application claims the benefit of U.S. patent application No. 61/413,170, filed on 12/11/2010.

This application is a continuation-in-part application of U.S. patent application No. 12/557,479 filed on 9/10/2009.

Technical Field

The disclosure herein relates generally to positioning systems. In particular, the present disclosure relates to wide area positioning systems. Background

Positioning systems like the Global Positioning System (GPS) have been used for many years. However, under poor signal conditions, these conventional positioning systems may have degraded performance.

Drawings

Fig. 1 is a block diagram of a wide area location system, under an embodiment.

Fig. 2 is a block diagram of a synchronization beacon, under an embodiment.

Fig. 3 is a block diagram of a positioning system using a repeater configuration, under an embodiment.

Fig. 4 is a block diagram of a positioning system using a repeater configuration, under an alternative embodiment.

Fig. 5 shows signal tower synchronization under an embodiment.

Fig. 6 is a block diagram of a GPS-governed PPS generator, under an embodiment.

Fig. 7 is a GPS-governed oscillator, under an embodiment.

Fig. 8 shows a signal diagram for counting time differences between a PPS and a signal that enables an analog portion of a transmitter to transmit data, under an embodiment.

Fig. 9 is a block diagram of a differential WAPS system, under an embodiment.

Fig. 10 illustrates co-view time transfer under an embodiment.

Fig. 11 illustrates two-way time transfer under an embodiment.

Fig. 12 is a block diagram of a receiver unit, under an embodiment.

Fig. 13 is a block diagram of an RF module, under an embodiment.

Fig. 14 illustrates signal up-conversion and/or down-conversion under an embodiment.

Fig. 15 is a block diagram of a receiver system with multiple receive chains, under an embodiment, where one of the receive chains may be temporarily used for receiving and processing a WAPS signal.

Fig. 16 is a block diagram illustrating a clock shared in a positioning system, under an embodiment.

Fig. 17 is a block diagram of assistance delivery from a WAPS to a GNSS receiver, under an embodiment.

Fig. 18 is a block diagram illustrating the transfer of assistance information from a GNSS receiver to a WAPS receiver, under an embodiment.

Fig. 19 is an example configuration of providing WAPS assistance information from a WAPS server, under an embodiment.

FIG. 20 is a flow diagram of estimating an earliest arriving path in h [ n ], under an embodiment.

Fig. 21 is a flow diagram of estimating a reference correlation function, under an embodiment.

Fig. 22 is a flow diagram of estimating a noise subspace, under an embodiment.

Fig. 23 is a flow diagram of estimating a noise subspace, under an alternative embodiment.

Fig. 24 is a flow diagram of estimating a noise subspace under an alternative embodiment.

Fig. 25 is a flow diagram of estimating a noise subspace under yet another alternative embodiment.

Fig. 26 is a flow diagram of estimating a noise subspace under yet another alternative embodiment.

Fig. 27 is a block diagram of a reference altitude pressure system, under an embodiment.

Fig. 28 is a block diagram of a WAPS integrated with a reference altitude pressure system, under an embodiment.

FIG. 29 is a block diagram of hybrid position estimation using range measurements from various systems, under an embodiment.

Fig. 30 is a block diagram of hybrid position estimation using position estimates from various systems, under an embodiment.

Fig. 31 is a block diagram of hybrid position estimation using a combination of range and position estimates from various systems, under an embodiment.

Fig. 32 is a flow diagram of a determination of a hybrid position solution under an embodiment in which position/velocity estimates from the WAPS/GNSS system are fed back to help calibrate the drift bias of the sensor from time to time when the GNSS/WAPS position and/or velocity estimates are of good quality.

FIG. 33 is a flow diagram of determining a hybrid position solution under an embodiment in which sensor parameters (e.g., bias, scale, and drift) are estimated as part of position/velocity calculations in GNSS and/or WAPS units without explicit feedback.

FIG. 34 is a flow diagram for determining a hybrid position solution, under an embodiment, in which sensor calibration is separated from individual position calculation units.

FIG. 35 is a flow diagram of determining a hybrid position solution under an embodiment in which sensor parameter estimation is performed as part of the state of the individual position calculation units.

Fig. 36 illustrates the exchange of information between the WAPS and other systems, under an embodiment.

Fig. 37 is a block diagram illustrating the exchange of location, frequency, and time estimates between an FM receiver and a WAPS receiver, under an embodiment.

Fig. 38 is a block diagram illustrating the exchange of location, time, and frequency estimates between a WLAN/BT transceiver and a WAPS receiver, under an embodiment.

Fig. 39 is a block diagram illustrating the exchange of location, time, and frequency estimates between a cellular transceiver and a WAPS receiver, under an embodiment.

Figure 40 shows a parallel complex correlator architecture under an embodiment.

FIG. 41 illustrates a 32-bit shift register implementation derived from two 16-bit shift register primitives with parallel random access read capability, under an embodiment.

Fig. 42 shows shift operation and read operation rates under an embodiment.

Fig. 43 illustrates, under an embodiment, a structure of an adder tree implementing a 1023 × n-bit adder.

Fig. 44 is a block diagram of session key setting under an embodiment.

Fig. 45 is a flow diagram of encryption, under an embodiment.

Fig. 46 is a block diagram of a security architecture for encryption, under an alternative embodiment.

Detailed Description

Systems and methods for determining a position of a receiver are described. The positioning system of an embodiment includes a network of transmitters including a transmitter that broadcasts a positioning signal. The positioning system includes a remote receiver that acquires and tracks positioning signals and/or satellite signals. The satellite signals are signals of a satellite based positioning system. The first mode of the remote receiver uses terminal-based positioning, wherein the remote receiver calculates the position using positioning signals and/or satellite signals. The positioning system includes a server coupled to a remote receiver. The second mode of operation of the remote receiver comprises network-based positioning, wherein the server calculates the position of the remote receiver from the positioning signals and/or satellite signals, wherein the remote server receives and communicates the positioning signals and/or satellite signals to the server.

The method of determining a position of an embodiment includes receiving at least one of a positioning signal and a satellite signal at a remote receiver. A positioning signal is received from a transmitter network comprising a plurality of transmitters. Satellite signals are received from a satellite-based positioning system. The method includes determining a location of a remote receiver using one of a terminal-based location and a network-based location. The terminal-based positioning includes calculating, at the remote receiver, a position of the remote receiver using at least one of the positioning signals and the satellite signals. The network-based positioning includes calculating, at a remote server, a position of the remote receiver using at least one of the positioning signals and the satellite signals.

In the following description, numerous specific details are introduced to provide a thorough understanding of and enabling description for the described systems and methods. One skilled in the relevant art will recognize, however, that the embodiments can be practiced without one or more of the specific details, or with other components, systems, etc. In other instances, well-known structures or operations are not shown or described in detail to avoid obscuring aspects of the disclosed embodiments.

Fig. 1 is a block diagram of a positioning system in the context of an embodiment. Positioning systems, also referred to herein as Wide Area Positioning Systems (WAPS) or "systems," include: a network of synchronization beacons; a receiver unit (and optionally with a location calculation engine) that acquires and tracks beacons and/or Global Positioning System (GPS) satellites; and a server including an index (index) of the signal tower, a charging interface (charging interface), a proprietary encryption algorithm (and optionally a site calculation engine). The system operates in a licensed/unlicensed band of operation and transmits dedicated waveforms for location and navigation purposes. The WAPS system may be used in conjunction with or to assist other positioning systems for better location solution (location solution). In the context of this document, a positioning system is a system that locates one or more of latitude, longitude and altitude coordinates.

In this document, whenever 'GPS' is mentioned, it is meant to refer to GNSS (global navigation satellite system) in a broader sense that may include other existing satellite positioning systems such as Glonass, as well as future positioning systems such as Galileo and Compass/Beidou.

Fig. 2 is a block diagram of a synchronization beacon, under an embodiment. The synchronization beacons (also referred to herein as beacons) of an embodiment form a CDMA network, and each beacon transmits a pseudo-random number (PRN) sequence, such as a gold code sequence, with good cross-correlation properties using a data stream of embedded assistance data. Alternatively, the sequences from each beacon transmitter may be staggered in time by separate time slots into a TDMA format.

In terrestrial positioning systems, one of the main challenges to overcome is the near-far (near-far) problem, where at the receiver, the far-range transmitter will be interfered with by nearby transmitters. To address this problem, the beacons of embodiments use a combination of CDMA and TDMA techniques, where the local transmitters may use separate time slots (TDMA) (and optionally different Codes (CDMA)) to mitigate the near-far problem. Allowing further away transmitters to use the same TDMA time slot while using different CDMA codes. This allows wide area scalability of the system. The TDMA time slots may be deterministic to ensure near-far performance or randomized to provide good average near-far performance. The carrier signal may also be shifted by some number of hertz (e.g. a fraction of the gold code repetition frequency) to improve the cross-correlation performance of the code to solve any "near-far" problem. When two signal towers use the same TDMA time slot but different codes, interference cancellation of the stronger signal can be used before the weaker signal is detected, further counteracting cross-correlation in the receiver.

Another important parameter in TDMA systems is the TDMA slot period (also referred to as TDMA frame). In particular, in a WAPS system, the TDMA frame duration is the time period between two consecutive time slots of the same transmitter. The TDMA frame duration is determined by the product of the number of transmitter time slots required to make a position fix in the coverage area and the TDMA time slot duration. The TDMA time slot duration is determined by the sensitivity requirements, although the sensitivity is not necessarily limited by a single TDMA time slot. One example configuration may use 1 second for the TDMA frame duration and 100ms for the TDMA slot duration.

In addition, the beacon of an embodiment may use a preamble that includes assistance data, or may use information for channel estimation and forward error detection and/or correction to help make the data robust. Assistance data of embodiments includes, but is not limited to, one or more of the following: the precise system time at the rising or falling edge of the pulse of the waveform; geocode data (latitude, longitude and altitude) for signal towers; geocode information of nearby signal towers and indices of sequences used by individual transmitters in the area; clock timing correction values for the transmitter (optional) and neighboring transmitters; local barometric pressure correction (optional); WAPS timing versus GNSS time (optional); indication of urban, semi-urban, rural environment of the secondary receiver in the pseudo-range solution (optional); and an offset from the base index or indices of the PN sequence to the gold code sequence. In a broadcast transmission data frame, a field may be included that contains information that disables a single or group of receivers for security and/or license management reasons.

The transmitted waveform timing from the transmissions of the different beacons and signal towers of an embodiment are synchronized to a common timing reference. Alternatively, the timing difference between transmissions from different signal towers should be known and transmitted. The assistance data is repeated at intervals determined by the number and size of the data blocks, except for timing messages that are to be incremented at regular intervals. As described in detail herein, the assistance data may be encrypted using a dedicated encryption algorithm. The spreading code may also be encrypted for additional security. The signal is up-converted and broadcast at a predefined frequency. The end-to-end delay in the transmitter is accurately calibrated to ensure that the differential delay between beacons is approximately less than 3 nanoseconds. Using a differential WAPS receiver at the site of investigation listening to a group of transmitters, the relative clock correction values for the transmitters in the group can be found.

The signal tower arrangement of the embodiments is optimized for coverage and site accuracy. The deployment of signal towers is arranged in such a way that signals are received from 3 or more signal towers at most sites within the network and at the edges of the network, such that the geometric dilution of precision (GDOP) in each of these sites is less than a predetermined threshold based on accuracy requirements. The software program for RF planning studies is extended to include analysis of GDOPs in and around the network. GDOP is a function of receiver position and transmitter position. One way to include GDOP in the network planning is to set the optimization as follows. The function to be minimized is the volume integral of the square of the GDOP over the coverage volume. The volume integrates the (x, y, z) coordinates for the receiver position. For limited n transmitter position coordinates (x) in a given coverage area₁,y₁,z₁)、(x₂,y₂,z₂)、…(xn_,yn_,z_n) Minimization is performed, transmitter position coordinates are in the coverage volume: for i =1_min＜x＜x_max、y_min＜y＜y_max、z_min＜z＜z_maxWherein x is_min、y_minAnd z_minIs the lower limit, x_max、y_maxAnd z_maxIs the upper limit of the coverage volume. The function to be minimized can be written as

In addition, the coverage area R can be determined according to_jThe importance of (i.e. the required quality of performance) the function to be minimized is weighted.

Additional restrictions on beacon coordinate locations may be based on the location of beacons that are already available in a given area. The co-ordinates of all the co-ordinates may be generally coordinated in a local horizontal co-ordinate system with the average east being positive x, the average north being positive y and the average vertical direction being positive z. Software that solves the above-described constrained minimization problem will output the optimal transmitter location (x) that will minimize the function f₁,y₁,z₁)、(x₂,y₂,z₂)、…(xn_,yn_,z_n)。

This technique may be applied for wide area networks (like in cities) or in local deployments (like in malls). In one example configuration, the network of transmitters is arranged in a triangle/hexagon around each metropolitan area, separated by a range of about 30 km. Each signal tower may radiate via a respective antenna in the range of approximately 20W to 1kW EIRP up to maximum power. In another embodiment, the signal tower may be located and may transmit at power levels as low as 1W. The operating frequency band includes any licensed or unlicensed frequency band in the radio spectrum. The transmit antennas of embodiments include omni-directional antennas or multiple antennas/arrays that may facilitate diversity, sectorization, etc.

Adjacent signal towers are distinguished using different sequences with good cross-correlation properties for transmission or alternatively the same sequence at different times. These discrimination techniques may be combined and applied only to a given geographic area. For example, the same sequence may be reused over networks in different geographic regions.

Local signal towers may be placed in a given geographic area to extend the wide area network signal towers of embodiments. When a local beacon is used, the local beacon may improve the accuracy of the location. Local signal towers may be deployed in an environment such as a campus, or separated by a distance (which may range from tens of meters up to several kilometers) for common security needs.

The signal towers are preferably placed at various heights (rather than at similar heights) to facilitate better quality altitude estimates from the location solution. Another way to add altitude diversity to a signal tower is to have multiple WAPS transmitters (using different code sequences) at different altitudes on the same physical signal tower (with the same latitude and longitude), except that the transmitters are at different latitudes/longitudes with different altitudes. Note that different code sequences on the same physical beacon can use the same time slot because transmitters on the same beacon do not create near-far problems.

The WAPS transmitter may be placed on an existing or new signal tower (e.g., a cellular signal tower) used by one or more other systems. By sharing the same physical signal tower or site, WAPS transmitter deployment costs can be minimized.

To improve performance in a local area (e.g., a warehouse or mall), additional signal towers may be placed in the area to extend the transmitters for wide area coverage. Optionally, to reduce the cost of installing a full transmitter, repeaters may be placed in the area of interest.

Note that the transmitted beacon signals used for positioning discussed above need not be built-in to the WAPS's unique transmitter, but may be signals from any other system that was originally synchronized in time or a system that has extended synchronization through an additional timing module. Alternatively, the signal may come from a system that can determine relative synchronization by a reference receiver. These systems may have, for example, already deployed or newly deployed additional synchronization capabilities. Examples of these systems may be broadcast systems such as digital and analog TV or MediaFlo.

When a WAPS network is configured, some transmit sites may be better (clutter, height of beacons above power level) than some other sites in the network as determined by design or by field measurements. The beacons may be identified by the receiver, either directly or indirectly, or by encoding data bits that indicate the "quality" of the beacons (which the receiver may use to weight the signals received from the beacons).

Fig. 3 is a block diagram of a positioning system using a repeater configuration, under an embodiment. The repeater configuration comprises the following components:

1) public WAPS receiving antenna (antenna 1)

2) RF power amplifier and splitter/switch connection for each WAPS transmitter antenna (local antennas 1-4)

3) WAPS subscriber receiver

The antenna receives the composite signal, amplifies it, and distributes (switches) it to the local antennas 1-4. The handover should (preferably) be done in such a way that there is no overlap (collision) of transmissions from different repeaters at the user receiver. Collisions of transmissions may be avoided by using a guard interval. The known cable delay from the switch to the transmit antenna should be compensated for by adding a delay at the repeater-amplifier-transmitter to equalize the overall delay for all local repeaters, or by adjusting the estimated time of arrival from a particular repeater to the cable delay at the user receiver. When TDMA is used in the wide-area WAPS network, the repeater slot switching rate is selected such that each wide-area slot (each slot will contain one wide-area WAPS signal tower) occurs in all repeater slots. One example configuration would use a repeater timeslot duration equal to a multiple wide area TDMA frame duration. Specifically, if the wide area TDMA frame is 1 second, the repeater time slot may be an integer number of seconds. This configuration is the simplest, but is only suitable for deployment in a limited small area because of the RF signal distribution requirements on the cable. The user WAPS receiver uses the time difference of arrival when listening to the repeater towers to calculate position and operates under a static (or quasi-static) assumption during the repeater slot cycle. The fact that the transmission is from a repeater can be automatically detected by the fact that each WAPS signal tower signal shows the same timing difference (hop) from one repeater time slot to the next.

Fig. 4 is a block diagram of a positioning system using a repeater configuration in the context of an alternative embodiment. In this configuration, each repeater includes a WAPS repeater-receiver and an associated coverage extension WAPS transmitter with a local antenna (which may be indoors, for example). The WAPS repeater-receiver should be able to extract WAPS system timing information and the WAPS data stream corresponding to one wide-area WAPS transmitter. The WAPS system timing and data corresponding to one wide-area WAPS transmitter is delivered to the corresponding local-area WAPS transmitter, which may then send the WAPS signal again (e.g., using a different code and the same time slot). The transmitter will include additional data in its transmission such as latitude, longitude and altitude of the local antenna. In such a configuration, WAPS user receiver operation (range measurement and position measurement) may be apparent to the fact that the signal comes from a repeater. Note that the transmitter used in the repeater is cheaper than a full WAPS beacon, as it does not need to have a GNSS timing unit to extract the GNSS timing.

Depending on the operating mode of the receiver unit, the system provides terminal-based positioning or network-based positioning. In terminal-based positioning, the receiver unit calculates the position of the user on the receiver itself. This is useful in applications like turn-by-turn navigation, geo-fencing, etc. In network-based positioning, a receiver unit receives signals from a signal tower and transmits or sends the received signals to a server to calculate the user's location. This is useful in applications like E911 and asset tracking and management by a central server. The position calculation in the server may be done in near real-time or post-processing using data from many sources (e.g., GNSS, differential WAPS, etc.) to improve accuracy at the server. The WAPS receiver may also provide and obtain information from a server (e.g., similar to a SUPL Secure User PLane server) to facilitate network-based positioning.

The signal towers of an embodiment remain synchronized with each other, either autonomously or using network-based synchronization. Fig. 5 shows the signal tower synchronization in the case of an embodiment. In describing aspects of synchronization, the following parameters are used:

system transmitter time = t_WAPS-tx

Absolute time reference = t_{WAPS_abs}

Time adjustment value = Δ_system=t_WAPS-tx-t_{WAPS_abs}

Note that it is not necessary to synchronize the WAPS system time with an absolute time reference. However, all WAPS transmitters are time synchronized to a common WAPS system (i.e., the relative timing of all WAPS transmitters is synchronized). The timing correction for each transmitter should be calculated relative to the WAPS system time (if any). The timing correction values should be made directly available to the receiver, either by assisted transmission over the air WAPS or by some other means of communication. For example, assistance may be delivered to the WAPS receiver from a system (e.g., Iridium (Iridium) or digital TV or MediaFlo or broadcast channel of a cellular system), through a cellular (or other) modem, or through broadcast data. Alternatively, the timing correction value may be sent to a server and used in calculating the position at the server. The beacon synchronization of the embodiment is described as follows.

Under network-based synchronization, signal towers are synchronized with each other in a local area. As described in detail herein, synchronization between signal towers typically includes transmission of pulses (which may be modulated using any form of modulation onto a carrier and/or spreading using a spreading code for a better time solution (which in turn modulates the carrier)) and synchronization to the pulse edges on the receiver.

In the autonomous synchronization mode of an embodiment, a local timing reference is used to synchronize the signal towers. The timing reference may be, for example, one of the following: a GPS receiver; a high accuracy clock source (e.g., atomic); a local time source (e.g., a GPS-governed clock); and any other network with a reliable clock source. The use of precisely time synchronized signals from XM satellite radio, LORAN, eLORAN, TV signals, etc. can be used as a coarse timing reference for the signal tower. As an example in one embodiment, fig. 6 is a block diagram of a PPS pulse source from a GPS receiver to specify an accurate/stable timing source such as Rubidium (Rubidium), cesium (Caesium), or hydrogen master (hydrogen master) in the context of an embodiment. Alternatively, as shown in fig. 7, a GPS (global positioning system) rubidium-conditioned clock oscillator may be used.

Referring to fig. 6, the time constant of the PLL in the accurate clock source is set to a sufficiently large number (e.g., in the range of 0.5-2 hours) to provide better short term stability (or equivalently filtering of short term GPS PPS changes), and the GPS-PPS provides longer term stability and wider area 'coarse' synchronization. The transmitter system continuously monitors the two PPS pulses (from the GPS unit and from an accurate clock source) and reports any anomalies. The anomaly may be that one of the PPS sources drifts away from the other source for a given time threshold determined by the signal tower network administrator after the two PPS sources lock for several hours. An anomaly may be detected using a third local clock source. In the case of abnormal behavior, the transmitter system selects the PPS signal that exhibits correct behavior, and this information is reported back to the monitoring station. Additionally, the instantaneous time difference between the PPS input and the PPS output of the accurate time source (as reported by the time source) may be broadcast by the transmitter or may be sent to the server for use in post-processing.

In the transmitter system, the time difference between the rising edge of the PPS pulse input and the rising edge of the signal that enables the analog part of the transmitter to transmit data is measured using an internally generated high speed clock. Fig. 8 shows a signal diagram that counts the time difference between a PPS and a signal that enables the analog components of the transmitter to transmit data, in the case of an embodiment. A count representing the difference is sent to each receiver as part of the data stream. Using a highly stable clock reference such as a rubidium clock (which is stable over several hours/days) enables the system to store/transmit the correction value for each signal tower on the device, only in cases where the device can no longer modulate the particular signal tower data. The correction data may also be transmitted to the device via a communication medium, if there is a communication medium available. The correction data from the signal tower may be monitored by a reference receiver or a receiver installed on the signal tower listening to other signal tower broadcasts and may be delivered to a central server. The signal towers may also periodically transmit the count information to a central server, which may then disseminate the information to devices in the vicinity of the signal towers via a communication link to the devices. Alternatively, the server may deliver the information from the signal tower (e.g., locally) to an adjacent signal tower, such that the information may be broadcast as assistance information for the adjacent signal tower. The assistance information for neighboring signal towers may include position (since the signal towers are static) and timing correction information about nearby signal towers.

Similar to the transmitter timing correction values of the embodiments, when a true PPS is available, it can be used to estimate multipath offset and accurate true range. The receiver uses samples of the signal, e.g., from the ADC, to estimate the range. The receiver of an embodiment uses a high speed clock to determine the difference between the occurrence of the PPS and the first edge of the sample ADC clock. This enables the range of the receiver estimated based on the ADC samples to be corrected for the difference between when the true PSS is present and when the ADC samples the data, thereby enabling the true range of the receiver to be estimated to a better accuracy than the sample clock solution of the ADC. In the context of the discussion in the above paragraph, PPS refers to a pulse that is aligned with an edge such as a GPS pulse-per-second (PPS) or has a known offset from a standard timing reference.

In another embodiment, a wide area differential positioning system may be used to correct for timing errors from the signal towers. Fig. 9 is a block diagram of a differential WAPS system, under an embodiment. A reference receiver (located at a previously surveyed site) is used to receive signals from all signal towers in the vicinity. Although the principle of differential GPS is applied in this method, the non-line-of-sight effects are handled in the ground situation so that they are unique. The pseudorange (code phase) measurements of the reference receiver for each tower are time-stamped and then sent to the server. The received code phase based range measured at the reference receiver for signal towers j and i can be written as follows:

wherein,is a reference receiver, dt, for the geometrical range of the tower j of the transmitted signal_refAnd dt^jRespectively, the offsets of the reference receiver and transmitter clocks relative to a common reference time (that is to say GPS time) in relation to the respective antennas of the reference receiver and transmitter, c is the speed of the light, andis the noise of the measurement.

By subtracting the above two equations and using the known geometric range from the reference receiver to the transmitting signal tower, the difference dt in clock timing between signal towers i and j is calculated at the serverⁱ-dt^j. This enables the elimination of transmissions in rover/mobile station measurementsTiming differences between the emitters. Note that averaging over time can be used to obtain a better (e.g., less noisy) time difference dt when the clock used in the transmit signal tower is relatively stableⁱ-dt^jAnd (6) estimating the value.

The pseudorange measurements of the rover/mobile station are also time-stamped and sent to the server. The received code phase based range measured at the rover/mobile station can be written as:

by subtracting the above two equations and rearranging, the result is

It is noted that,andis a measured quantity, the quantity dt being calculated from a reference receiver measurementⁱ-dt^j. Can be written in terms of the unknown coordinates of the receiver and the known coordinates of the towers i and j of the transmitted signalAndeach of which. Using three range measurements, a two range difference equation may be formed as above to obtain a two-dimensional position solution, or using four range measurementsThree range difference equations may be formed as above to obtain the three-dimensional position. Using additional measurements, a least squares solution may be used to quantify the noiseAndthe effect of (a) is minimized.

Alternatively, the timing difference correction value may be sent back to the mobile station to correct for the error in place and to facilitate position calculations at the mobile station. The differential correction values can be applied to as many transmitters as can be seen by both the reference and the mobile station. This approach may conceptually enable the system to operate without signal tower synchronization, or alternatively correct for any residual clock error in a loosely synchronized system.

In contrast to the differential approach above, another approach is an independent timing approach. One way to establish timing synchronization is to have the GPS timing receiver at each transmit signal tower in a particular area receive DGPS correction values from a DGPS reference receiver in the same area. A DGPS reference receiver installed at a known location sees its own clock as the reference clock and finds a correction to the pseudorange measurements of the GPS satellites tracked to it. The DGPS corrections for a particular GPS satellite typically include the total error due to satellite position and clock errors, as well as ionospheric and tropospheric delays. Because the direction of the line of sight between the DGPS reference receiver and the GPS satellites does not change much within this vicinity, the overall error is the same for any pseudorange measurements made by other GPS receivers in the vicinity of the DGPS reference receiver (typically in an area centered on the DGPS receiver with a radius of about 100 Km). Thus, a GPS receiver using a DGPS correction value transmitted by a DGPS reference receiver for a particular GPS satellite uses the correction value to remove the overall error from its pseudorange measurements for that satellite. However, in this process, it adds the clock offset of the DGPS reference receiver with respect to GPS time to its pseudorange measurement. However, since this clock offset is common to all DGPS pseudorange correction values, its effect on the timing solutions of the different GPS receivers will be a common offset. However, the common offset does not give relative timing error in the timing of different GPS receivers. In particular, if these GPS receivers are clocked GPS receivers (at known locations), they are all synchronized to the clock of the DGPS reference receiver. When these GPS timing receivers drive different transmitters, the transmissions are also synchronized.

Instead of using the corrections from the DGPS reference receiver, the GPS timing receivers can use similar corrections sent by Wide Area Augmentation System (WAAS) satellites to synchronize the transmissions of their driven transmitters. The advantage of WAAS is that the reference time is not the reference time of the DGPS reference system, but the GPS time itself, which is maintained by an accurate set of atomic clocks.

Another approach to achieving accurate time synchronization between signal towers across a wide area is to use a time transfer technique that establishes timing between pairs of signal towers. One technique that may be applied is referred to as "common viewtime transfer". Fig. 10 illustrates co-view time transfer under an embodiment. A GPS receiver in a transmitter with a common view of satellites is used for this purpose. The GPS receiver periodically (e.g., at least once every few seconds) time tags code phase and/or carrier phase measurements from each signal tower of satellites in common view and sends them to a server where they are analyzed.

Can observe the GPS code(the signals transmitted by satellite "i" and observed by receiver "p") are written as:

wherein,is equal toThe geometric range of the receiver satellites of (a),is the receiver antenna position at the time of signal reception,indicating the satellite position at the time of signal transmission,andrespectively ionospheric and tropospheric delays, andandis the receiver and satellite hardware group delay. Variables ofIncluding the effect of the antenna, the cable connecting it to the receiver, and the delay within the receiver itself. Further, dt_pAnd dtⁱReceiver and satellite clock offsets relative to GPS time, c is the speed of the light, and ε_RIs the measurement noise.

Method for transmitting common view time to calculate single difference code observed valueWhich is the difference between code observations measured simultaneously at two receivers (referred to as "p" and "q"), which is

In calculating the single-difference observations, the group delays in the satellites and the clock errors of the satellites are cancelled out. Further note that in the above equations, tropospheric and ionospheric perturbations are cancelled out (or can be modeled, for example, in the case of large receiver separation). Once the group delay differences between the receivers are calibrated, the desired time difference between the receiver clocks, c (dt), can be obtained from the equation_p-dt_q). The single difference and the satellite measurements across multiple times may be combined to further improve the quality of the estimated time difference.

In a similar manner, the single difference carrier phase equation for the common view time transfer can be written as:

note that since there is initial phase ambiguity and integer ambiguity in the above equation, the time transfer cannot be directly determined using phase single difference. The combined use of code and phase observations enables the use of absolute information about the time difference from the code and accurate information about the evolution of the time difference from the carrier phase. The error variation in carrier phase single difference is significantly better than code phase single difference, which results in better time transfer tracking.

The error for each tower obtained for a given satellite is sent back to the tower for correction, applied at the tower, sent to the receiver over a communication link, additionally corrected by the receiver, or sent as a broadcast message along with other timing correction values from the tower. In a specific example, measurements from signal towers and receivers may be post-processed at the server for better position accuracy. A single channel GPS timing receiver or a multi-channel timing receiver that produces C/a code measurements and/or carrier phase measurements from L1 and/or L2 or from other satellite systems such as Galileo/Glonass may be used for co-view time transfer purposes. In a multi-channel system, the receiver acquires information from multiple satellites in common view at the same instant.

An alternative mechanism in "co-view time transfer" is to ensure that different timing GPS receivers in the local area, each feeding its respective transmitter, use only a common satellite in their timing pulse derivation (e.g., one pulse per second), without attempting to correct the timing pulse to GPS (or UTC) second alignment. The use of common view satellites ensures that common errors in the timing pulses (e.g., common GPS satellite position and clock errors and ionospheric and tropospheric delay compensation errors) produce errors in the timing pulses of about the same magnitude and that the relative errors in the timing pulses are reduced. Since there is only a relation to the timing error when performing positioning, there is no need to perform any server-based timing error correction. However, the server may give commands to different GPS receivers of the GPS satellites to be used in deriving the timing pulses.

An alternative method of time transfer is the "two-way time transfer" technique. Fig. 11 shows a two-way time transfer in the case of an embodiment. Consider two signal towers for timing against each other. The transmission from each of the two transmitters starts on a PPS pulse and a time interval counter is started on the receive part (WAPS receiver) of the transmit tower. The received signal is used to stop the interval counter on either side. The results from the time interval counter are sent over the data modem link to the WAPS server where they are compared together with the time of transmission and the error in timing between the two signal towers can be calculated. This can then be extended to any number of signal towers. In this method, a counter at signal tower i may be measuredMagnitude Δ T_iAnd the counter measurement Δ T at Signal Tower j_jThe relationship between and the time difference dt between the clocks in i and j_ijIs shown as

Wherein,is a transmitter delay of a signal tower, andis the receiver delay of the signal tower. Once the transmitter and receiver delays are corrected, the time difference can be estimated.

In addition to time transfer between signal towers, the timing of the signal towers relative to GPS time may also be derived by GPS timing receivers used in co-view time transfer. Using range measurements as

Calculating a time correction value dt of a local clock relative to GPS time after taking into account delay of a receiver, satellite clock errors and ionosphere/troposphere errors_p. The delay delta of the receiver can be measured by the group delay_R,pAnd (6) carrying out calibration. The information from the GPS satellite navigation messages (obtained by demodulation or from a server) can be used to calculate the cancellation dtⁱAndthe satellite timing correction value of (2). Similarly, tropospheric and ionospheric delay effects are minimized using correction values from the external model. The ionospheric correction values may be obtained, for example, from WAAS messages. Alternatively, when available, corrections can be made from the RTCM DGPS for pseudorangesPositive values, a combination of clock and ionosphere/troposphere correction values are obtained.

The offset relative to GPS time may also be transmitted as part of the data stream from the beacon. This enables any WAPS receiver that acquires WAPS signals to provide accurate GPS time and frequency, which helps to significantly reduce GNSS search requirements in GNSS receivers.

In an embodiment of the system, a broadcast transmitter may be utilized exclusively to provide localized indoor location determination. For example, in fire safety applications, the WAPS transmitters may be placed on three or more broadcast stations (which may be fire trucks, for example). The signal towers are synchronized to each other by one of many ways described earlier and the broadcast signal. The bandwidth and cut rate are scaled based on the spectral availability and accuracy requirements in the region for the application at that time. The receiver will be informed of the system parameters via the communication link to the device.

Fig. 12 is a block diagram of a receiver unit in the case of an embodiment. The beacon signal is received at an antenna on the receiver unit, down-converted (demodulated) and decrypted and fed to a positioning engine. The receiver provides all the information to accurately reconstruct the signal. The receive antennas may be omni-directional antennas or, alternatively, multiple antennas/arrays providing diversity or the like. In another embodiment, the mixing and down-conversion may be performed in the digital domain. Each receiver unit includes or uses a unique hardware identification number and a computer generated private key. Typically, each receiver unit stores the last few locations in non-volatile memory, and each receiver unit can then be remotely queried for the last few locations stored. Based on the availability of the spectrum in a given region, the transmitter and receiver can be adapted to the available bandwidth and the cut rate and filter bandwidth are varied for better accuracy and demultiplexing.

In one embodiment, digital baseband processing of the received signal is accomplished by multiplexing/feeding the signal from the GPS rf section with a WAPSRF module using commercially available GPS receivers. Fig. 13 is a block diagram of a receiver with a WAPS RF module, under an embodiment. The RF module includes one or more of a Low Noise Amplifier (LNA), a filter, a down-converter, and an analog-to-digital converter, to name a few. In addition to these components, additional processing on a chip or custom ASIC or FPGA or on a DSP or microprocessor may be used to further condition the signal to match the input requirements of the GPS receiver. The signal conditioning may include: digital filtering of in-band or out-of-band noise (e.g., ACI adjacent channel interference); converting an intermediate or baseband frequency of the input of the GPS IC according to the frequency of the WAPS receiver; adjusting the digital signal strength to enable the GPS IC to process the WAPS signal; an Automatic Gain Control (AGC) algorithm for controlling the WAPS front end, etc. In particular, frequency translation is a very useful feature, as it enables the WAPS RF module to work with any commercially available GPS receiver. In another embodiment, the entire RF front-end chain including the signal conditioning circuitry of the WAPS system may be integrated into an existing GPS substrate containing the GPS RF chain.

In another embodiment, if access to the digital baseband input cannot be used, the signal can be up/down converted from any frequency band to the GPS band and fed into the RF part of the GPS receiver. Fig. 14 illustrates signal up-conversion and/or down-conversion under an embodiment.

In another embodiment, multiple RF chains or tunable RF chains may be added to both the transmitter and receiver of the WAPS system, whether in a wide area or a local area, to use the most efficient frequencies operating in a given area. The choice of frequency may be determined by the cleanliness of the spectrum, propagation requirements, etc.

Similarly, the WAPS may temporarily use a receive chain in a receiver system that includes multiple receive chains. For example, a wideband CDMA (W-CDMA) receiver system includes two receive chains to improve receive diversity. Thus, when a WAPS is used in a W-CDMA receiver system, one of the two local receive chains of W-CDMA may be temporarily used for receiving and processing the WAPS signal. Fig. 15 is a block diagram of a receiver system with multiple receive chains, where one of the receive chains may be temporarily used to receive and process WAPS signals, under an embodiment. In this example, the WAPS signal may be temporarily received and processed using a diversity receive chain. Alternatively, a GPS receive chain may be used to temporarily receive and process WAPS signals.

The radio front end may be shared between the WAPS and another application. Some parts of the front end may be shared and some parts may be used on a mutually exclusive basis. For example, if a substrate (die)/system already has a TV (NTSC or ATSC or DVB-H, MediaFLO like system) tuner front-end that includes an antenna, the TV tuner radio and antenna can be shared with the WAPS system. They may operate on a mutually exclusive basis in that the system receives either TV signals or WAPS signals at any given time. In another embodiment, if it is made easier to add the WAPS RF part to such a system, the antenna can be shared between the TV tuner and the WAPS system, which enables both systems to operate simultaneously. In the case of a system/substrate with radios like FM radios, the RF front end can be modified to include both WAPS systems and FM radios, and these radios can operate on a mutually exclusive basis. Similar modifications can be made to systems having some RF front-ends operating at near frequencies near the WAPS RF band.

A clock source reference, such as a crystal, crystal oscillator (XO), voltage controlled temperature compensated crystal oscillator (VCTCXO), digitally controlled crystal oscillator (DCXO), temperature compensated crystal oscillator (TCXO), for the GNSS subsystem may be shared with the WAPS receiver to provide a reference clock to the WAPS receiver. The sharing may be done on the substrate or off-chip. Alternatively, any other TCXO/VCTCXO system used on a cellular phone may be shared with the WAPS system. Fig. 16 is a block diagram illustrating clock sharing in a positioning system, under an embodiment. Note that the transceiver or processor system block may refer to a variety of systems. The transceiver system that shares the clock with the WAPS system may be a modem transceiver (e.g., a cellular or WLAN or BT modem) or a receiver (e.g., a GNSS, FM or DTV receiver). These transceiver systems may optionally control a VCTCXO or DCXO for frequency control. Note that the transceiver system and WAPS system may be integrated into a single substrate, or may be separate substrates, and do not affect clock sharing. The processor may be any CPU system (e.g., ARM subsystem, digital signal processor system) using a clock source. In general, when sharing a VCTCXO/DCXO, the frequency corrections applied by other systems may be slowed down as much as possible to facilitate WAPS operations. In particular, frequency updates within the maximum integration time (integration time) being used in the WAPS receiver may be limited to allow the WAPS receiver to have better performance (i.e., minimize SNR loss). Information about the state of the WAPS receiver (in particular, the level of integration being used, acquisition of tracking states relative to the WAPS system) can be exchanged with other systems to better adjust the frequency update. For example, the frequency update may be suspended during the WAPS acquisition phase, or may be scheduled while the WAPS receiver is in a sleep state. The communication may be in the form of control signals or, alternatively, messages exchanged between the transceiver system and the WAPS system.

The WAPS broadcasts signals and messages from signal towers to support both the WAPS and the conventional GPS system in a manner that does not require modifications to the baseband hardware of the conventional GPS receiver. The importance of this is the fact that while the WAPS system has only half the available bandwidth as a GPS C/a code system (which affects chip rate), the WAPS broadcast signal is configured to operate within range of a commercial C/a code GPS receiver. Further, based on signal availability, the algorithm will decide whether GPS signals should be used to determine location, or WAPS signals, or a combination thereof, should be used to obtain the most accurate location.

In the case of a hybrid GNSS-WAPS usage scenario, assistance information for GNSS may be sent using data sent on top of gold code on the WAPS system. Assistance may be in the form of SV orbital parameters (e.g., ephemeris and almanac). Assistance may also be specific to SVs visible in a local area.

In addition, timing information obtained from the WAPS system may be used as fine time to assist the GNSS system. Since the WAPS system timing is aligned with GPS (or GNSS) time, code and bit alignment with the WAPS signal and reading the data stream from any signal tower provides a rough understanding of GNSS time. In addition, the position solution (the receiver's clock bias is a byproduct of the position solution) accurately determines the WAPS system time. Once the WAPS system time is known, the GNSS receiver may be provided with a fine time of assistance. Timing information may be conveyed using a single hardware signal pulse whose edges are tied to the internal timing of the WAPS. Note that WAPS system time is mapped directly onto GPS time (more generally GNSS time is used, since the time base of the GNSS system is directly related). The GNSS should be able to lock its internal GNSS time base count when the edge is received. Alternatively, the GNSS system should be able to generate pulses with edges aligned with its internal time base, and the WAPS system should be able to lock on to its internal WAPS time base. The WAPS receiver then sends a message with this information to the GNSS receiver, which enables the GNSS receiver to map its time base to the WAPS time base.

Similarly, the frequency estimate of the local clock may be used to provide a frequency for aiding the GNSS receiver. Note that the frequency estimate from the WAPS receiver may be used to refine the frequency estimate of the GNSS receiver, whether or not they share a common clock. When two receivers have separate clocks, additional calibration hardware or software blocks are required to measure the clock frequency of one system relative to the other. The hardware or software block may be in the WAPS receiver portion or in the GNSS receiver portion. The frequency estimate from the WAPS receiver may then be used to improve the frequency estimate of the GNSS receiver.

The information that may be sent from the WAPS system to the GNSS system may also include an estimate of the location. The estimate of the location may be approximate (e.g., determined by the PN code of the WAPS signal tower) or more accurate based on an estimate of the actual position in the WAPS system. Note that the location estimate available from the WAPS system may be combined with another position estimate from a different system (e.g., a coarse position estimate from a cellular ID based positioning) to provide a more accurate position estimate that may be used to better assist the GNSS system. Fig. 17 is a block diagram of assistance delivery from a WAPS to a GNSS receiver, under an embodiment.

The GNSS receiver may also help improve the performance of the WAPS receiver in terms of Time-To-First-Fix (TTFF), sensitivity, and location quality by providing location, frequency, and GNSS Time estimates To the WAPS receiver. As an example, fig. 18 is a block diagram illustrating the transfer of assistance information from a GNSS receiver to a WAPS receiver, under an embodiment. Note that the GNSS system could equally be replaced by LORAN, e-LORAN, or similar terrestrial positioning system. The location estimate may be partial (e.g., altitude or 2-D position) or complete (e.g., 3-D position), or raw range/pseudo-range data. Range/pseudorange data should be provided with the location of the SV (or the device that calculates the location of the SV, such as the SV orbit parameters) to enable use of the range information in the hybrid solution. All location assistance information should be provided together with a metric indicating the quality of the location assistance information. When providing GNSS time information (which may be communicated to the WAPS system using hardware signals), an offset of GNSS time relative to GPS time (if any) should be provided to enable use in the WAPS receiver. The frequency estimate may be provided as an estimate of the clock frequency, along with a confidence metric (indicative of the estimated quality of the estimate, e.g., the maximum expected error in the estimate). This is sufficient when GNSS and WAPS systems share the same clock source. When the GNSS and WAPS systems use separate clocks, the GNSS clocks should also be provided to the WAPS system to enable the WAPS system to perform calibration (i.e., estimate the relative clock bias of the WAPS with respect to the GNSS clocks), or alternatively, the WAPS system should provide its clocks to the GNSS system and the GNSS system should provide an estimate of the calibration (i.e., an estimate of the relative clock bias of the WAPS with respect to the GNSS clocks).

To further improve the sensitivity and TTFF of the WAPS receiver, the assistance information may be provided from the WAPS server to the WAPS receiver over other communication media (such as cellular phone, WiFi, SMS, etc.) (e.g., the assistance information may be decoded in other ways based on information transmitted by the signal tower). With the "almanac" information already available, the operation of the WAPS receiver is simplified, since the receiver only needs to align time with the transmitted waveform (no bit alignment or decoding is required). The elimination of the need to decode the data bits reduces TTFF, thus saving power since the receiver does not need to be continuously powered to decode all bits. Fig. 19 is an example configuration for providing WAPS assistance information from a WAPS server, under an embodiment.

Beacons may be added to the receiver to further improve local area positioning. The beacon may include a low power RF transmitter that periodically transmits a waveform with a signature based on the device ID. For example, the signature may be a code that uniquely identifies the transmitter. An associated receiver will be able to find the location of the transmitter with relatively higher accuracy, either by signal energy peak finding as it scans in all directions, or by direction finding (using signals from multiple antenna elements to determine the direction of arrival of the signal).

Scheme for multipath signals

The multi-path scheme is critical in positioning systems. Wireless channels are often characterized by a set of multipath components with random changes in phase and amplitude. To make the location accurate, the receiver algorithm is forced to resolve the line of sight (LOS) path if one exists (it will be the first path to arrive) or the first path to arrive (it may not necessarily be the LOS component).

Conventional methods often work as follows: (1) cross-correlating the received signal with a transmitted pseudo-random sequence (e.g., a gold code sequence known at the receiver); (2) the receiver locates the first peak of the obtained cross-correlation function and estimates that the timing of the first arriving path is the same as indicated by the position of that peak. These methods work efficiently as long as the minimum demultiplexing (multipath separation) is much larger than the inverse of the available bandwidth, which is often not the case. Bandwidth is a valuable commodity and a method that can solve multipath with the least amount of bandwidth is highly desirable to improve the efficiency of the system.

Depending on the channel environment (including multipath and signal strength), an appropriate method for obtaining an estimate of the earliest arriving path is used. For an optimal solution, a high resolution method is used, whereas for reasonable performance at low SNR, a more traditional method is applied that directly uses some properties of the cross-correlation peak samples and the correlation function around the peak.

Consider the rate f given by_sSampled quantized received signal y [ n ]]：

Wherein, y [ n ]]Is a received signal which is a transmitted pseudo-random sequence x n]And the effective channel Wherein h is_tx[n]Is a transmit filter, h_tx[n]Is a receive filter, and h [ n ]]Is a multipath channel.

One way to find the peak position is to interpolate the peak using values that surround the apparent peak position. The interpolation may be second order using a value on either side of the peak, or may use a higher order polynomial using two or more samples around the peak, or may use the most appropriate actual pulse shape. In the case of second order interpolation, the second order is fitted to the peak and the values immediately surrounding the peak. The peak of the second order determines the peak position for ranging. This approach is quite robust and can work well with low SNR.

Alternative embodiments may use values other than the peak position as the reference position. Note that the DLL actually uses the peak position as a reference position on the correlation function, whereas this method uses a point other than the peak as a reference. This method is motivated by the fact that the early edges of the correlation peaks are less affected by multipath than the trailing edges. For example, a chip T from a peak on a correlation function without distortion (no channel effects) may be used_cPoint 75% of (a) is taken as a reference point. In this case, the interpolated z [ n ] matching the 75% point is selected]Part of the function and finding a T with a peak of 25% away from this point_c. Another alternative peak correlation function based approach may use a peak shape (such as a measure of the distortion of the peak, e.g., the peak width). Starting from the peak location, a correction value to the peak location is determined based on the shape of the peak to estimate the earliest arrival path.

High resolution methods are a class of efficient multi-path resolution methods that use eigen-spatial decomposition to locate multi-path components. Methods such as MUSIC, ESPIRIT, etc. fall under this type of solution. They are very powerful solutions because, for the same given bandwidth, they can effectively solve multipath components that are spaced much closer together than in conventional approaches. The high resolution earliest time of arrival method attempts to directly estimate the earliest path time of arrival without inferring the peak position from the peak. In the following it is assumed that a rough acquisition of the transmitted signal is already available at the receiver and that the start of the pseudo-random sequence is approximately known at the receiver.

FIG. 20 is a flow chart of estimating the earliest arriving path in h [ n ], under an embodiment. The method of determining the earliest path includes, but is not limited to:

1. the received samples y [ n ] are cross-correlated with the transmitted sequence x [ n ] to obtain a result z [ n ]. When the cross-correlation is written as a convolution,

this equation can be rewritten as

Wherein phi is_xx[n]Is the autocorrelation function of a pseudorandom sequence

2. For z [ n ]]Is located and is denoted as n_peak. Extraction of z [ n ]]The wL samples to the left of the peak and the wR samples to the right of the peak, and the vector is denoted pV.

pV=[z[n_peak-wL+1]…z[n_peak+wR]]

Vector pV represents the cross-correlation result z n]The useful part of (a). In the ideal case, w is chosen when there is no channel distortion, and when the channel BW is not restricted_L=w_R=f_sT_cIt will be sufficient to determine the timing of the received signal. In the presence of limited BW, for when pseudo-random code x [ n ]]In the case of +1/-1 sequences, the best way to select wL and wR is to select them to be present in each caseNon-zero values (or more generally, selected values) to the left and right of the peak of>A specific threshold defined as a fraction of the peak). Another consideration when choosing wL and wR is to choose noise samples that are not correlated enough to obtain enough information about the noise subspace. In addition, the integers wL and wR should be chosen to include all possible multipath components, particularly on the left side (i.e., by choosing wL), to help solve for non-negativesThe long multipath component. Including too much more than f_sT_cThe amount of noise introduced in the pV vector increases, so samples must be reduced. By simulation and experimentation, the set of values for wL and wR is typically 3f_sT_cAnd 3f_sT_c。

Note that z [ n ]](in turn pV) comprises a channel h [ n ]]And a transmission filter h_tx[n]Reception filter h_rx[n]And the autocorrelation function phi of the pseudo-random sequence_xx[n]The influence of (c). To estimate the earliest arriving path in a channel, other effects need to be eliminated. In many cases, the transmit and receive pulse shapes are matched for optimal noise performance, but this limitation is not required for the algorithm to work. Defining the reference correlation function as requiring estimation and elimination before the earliest arriving path can be estimated using pV

3. Next, a reference correlation function phi is estimated_ref[n]。

One way to obtain the reference cross-correlation is as follows: steps 1-2 are performed on the ideal path (the so-called "wired link") to obtain the corresponding peak vector pV_Ref。pV_RefComprising a reference correlation function phi_ref[n]Is used to obtain a useful sample. Fig. 21 is a flow chart of estimating a reference correlation function in the case of an embodiment.

The "wired link" method involves sending a modulated signal from a transmitter front end (bypassing the power amplifier and transmit antenna) to a receiver front end (bypassing the receive antenna) over an 'ideal' channel (e.g., cable). Note that the 'ideal' channel may have some delay and attenuation, but should not add any other distortion, and must have a high SNR. To obtain the best performance, a 'wired' reference needs to be generated separately for each pseudo-random sequence, since they have different autocorrelation functions and therefore different references. Then, to obtain the best autocorrelation function, it is also critical to choose PRNs correctly (in particular, their closure in the autocorrelation sidelobes should be suppressed sufficiently compared to the peak), which will result in the best overall performance of the timing solution, since the autocorrelation sidelobes may falsify the multipath unless sufficiently attenuated. Assuming control of the transmit filter response, each receiver needs to calibrate the response over the wired link once during production. If the receiver filter characteristics can be controlled (e.g., for a batch of receivers), the calibration of the wired link for the response can be further reduced to one calibration measurement for a group of receivers.

Determining a reference correlation function phi_ref[n]An alternative method of (2) is to compute each component phi analytically_xx[n]、h_tx[n]And h_rx[n]And convolving them to arrive at the reference correlation function phi_ref[n]. Note that this approach depends on how much the transmit and receive filter impulse responses can be controlled in a practical implementation.

4. The SNR in the estimate of pV is improved by coherently averaging across multiple gold codes, even across multiple bits. Averaging across multiple bits may be done coherently after making a decision to transmit each bit. In other words, decision feedback is used before integrating across bits. Note that by performing averaging in the cross-correlation function estimation in step 1, an improved SNR can be equivalently obtained.

5. Using N_fftZero padding of- (wL + wR) zeros to calculate pV and pV_RefLength N of_fftTo obtain the length N, respectively_fftVector pV_FreqAnd pV_Ref,Freq. Obtaining N by checking the resolvability of the multipaths by simulation using both the synthetic and real measurement channels_fftThe optimum value of (2). Discovery of N_fftIs greater than or equal to 4096.

6. ComputingWith a channel h [ n ]]To obtain a frequency domain estimate (mixed with noise). If N is used_os(i.e. for transmit pulse shapes with band limits of +/-1/Tc,) For the received sequence y [ n ]]Oversampling is performed and if the transmit and receive pulse shape filters are perfectly band limited with BW =1/Tc, then for the real channel H_real[k]Estimation of (H)_full[k]Just around the DC ofThe positive and negative samples are non-zero (ready to use). From our studies, we conclude that either side of the DC should be picked up for optimal performance of the solution algorithmSamples based on the actual pulse shape filters used at the transmitter and receiver and the autocorrelation function phi_xx[n]selecting alpha > 1, note, including phi_ref[n]however, selecting too large α will result in a loss of signal information, when implemented, using a preferred choice of a =1.25 for the true band limiting function based on a raised cosine filter shape with small extra bandwidth.

7. If H is present_full[k]Is at index 0, then the H vector H [ 2 ] to be reduced]Is defined as:

H=[H_full[N_fft-N+1]…H_full[N_fft]H_full[0]H_full[1]…H_full[N]]

8. a matrix P is formed from the restored channel estimate vectors H k,

where 1 < M < 2N is a parameter and ()' represents the conjugate of the complex number.

Defining the covariance matrix R of the estimates of the restored channel estimate vector Hk as

R=P×P'

If the chosen M is too small (close to 1), the number of eigenvalues of R is very limited, as a result of which high resolution algorithms cannot be drawn between the signal and the noise. If the selected M is too large (close to 2N), the covariance matrix estimate R is unreliable because the amount of averaging in obtaining the covariance is insufficient and the obtained covariance matrix R is rank deficient. Therefore, a value of M in the middle of the allowable range of M, i.e., M = N, is a good choice. This was also verified empirically.

9. As the following expression, R is subjected to Singular Value Decomposition (SVD)

R=UDV＇

Where U is the matrix of left singular vectors, V is the matrix of right singular vectors, and D is the diagonal matrix of singular values.

10. Constructing a vector sV of sorted singular values as

sV = diagonal elements of D sorted in descending order

11. The next key step is to separate the signal and noise subspaces. In other words, to select the index ns in the vector sV, the singular value sV [ ns +1 ] is made]…sV[N]Corresponding to the noise. Defining vectors of noise singular values as sV_noise。

There are several methods that can separate the singular values corresponding to the noise subspace and find a representation of the basis vector of the noise subspace:

a) all are less thanOf (a), wherein T₁Is a threshold value, T, as a function of the signal-to-noise ratio (e.g. on-chip SNR)₁=f(SNR)。

FIG. 22 is a flow diagram of estimating a noise subspace, under an embodiment.

b) All are less thanWhere L is a parameter that can be selected to be greater than the delay spread (e.g., N/2), and T is₂Is another threshold value (a typical value may be 1000) that is determined empirically.

Fig. 23 is a flow diagram of estimating a noise subspace, under an alternative embodiment.

c) Another method includes determining a noise subspace by repeatedly estimating SNR for different intervals of the noise and signal plus noise subspaces and comparing with another estimated value of SNR. FIG. 24 is a flow chart of estimating a noise subspace in the case of another alternative embodiment.

1) The estimated value of SNR is calculated as follows:

i. suppose noise is represented by sV () n_s,n_s+1 … M, then the noise variance is calculated as:

asCalculating signal power

Estimate of snr:

2) alternative estimates of SNR are obtained by other methods, such as on-chip SNR. One method of directly estimating the SNR is as follows:

i. if the product is passed through X_iGiven the received data samples (after frequency error removal and resampling and code decorrelation of the samples for Tc space) (where X_iIs chip-spaced starting from the interpolated peak position).

X_i=,S+N_i

AsEstimating a signal

As aEstimating noise

AsEstimating SNR

3) The noise singular value is selected as sV (ns, ns +1, …, M) satisfying the following condition:

d) another method includes repeatedly estimating SNR for different intervals of the noise and signal subspace by using c)1), and selecting interval n_startSo that

To determine the noise subspace.

FIG. 25 is a flow chart of estimating a noise subspace in the case of yet another alternative embodiment.

e) FIG. 26 is a flow chart of estimating a noise subspace in the case of yet another alternative embodiment.

1) Definition ofThe first wLen singular value then represents the significant signal plus noise subspace or noise subspace singular values (the remaining singular values represent the correlated noise and signal and the quantization effect).

2) The estimated value of SNR is calculated as follows:

i. suppose the noise is represented by sV (i): i = n_s,n_s+1 … wLen; 1 < n_swLen, then the noise variance is calculated as:

asCalculating signal power

Estimate of snr:

3) definition of

n_start= [ minimum n)_s:SNR_est(n_s)＞(SNR_est(wLen)-thresDB)]. Then, n up to winLen_startRepresenting the singular values of the noise. the general value of thressdb is 10.

12. Selecting corresponding noise right singular vectors to establish V_NI.e. selecting all vectors in V corresponding to noise singular values and building a noise subspace matrix V_N。

13. Estimated time of arrival for the first path:

a) definition of

b) Range of values for τ (τ e τ_max,-τ_max]) CalculatingThe solution Δ τ of the small search may be chosen as desired. As an example, τ_max=5, and Δ τ =0.05, so as to be in the range [ -5, in steps of 0.05]Where τ is searched.

14. The peak of Ω (τ) will provide the channel pulse relative to the coarse peak n_peakThe position of (a). Theoretically, the first peak would correspond to the LOS path. τ can be controlled based on information about the propagation environment from the base station, possibly encoded in the transmission_max. For example, if the delay spread is large, τ may be increased_maxIs chosen to be larger (e.g., 10), and if the delay spread is smaller, τ may be chosen to be larger_maxA smaller value (e.g., 4) is selected.

The combination method comprises the following steps:

in addition to the individual methods discussed above, a wide variety of other combinations of methods may be used. The combination of on-chip SNR based schemes is an efficient approach. The following describes a list of combining schemes that can be implemented in practice:

1. for chipsnrs smaller than chipnrref, method 12(d) is chosen to select noise singular values. Otherwise, method 12(a) is selected.

2. For chipsnrs larger than chipnrref, method 12(d) is chosen to select the noise singular value and estimate the peak position. Otherwise, a direct peak estimation technique (e.g., peak interpolation, peak shape) is used starting from the cross-correlation function z [ n ].

3. For chipsnrs smaller than chipnrref, method 12(e) is chosen to select the noise singular value. Otherwise, method 12(a) is selected.

A typical value for chipSNRRef is 10 dB.

Calculation of position

The location of the receiver unit is determined by a positioning engine available on the terminal unit or the server. The receiver may use range measurements from the system or combine system range measurements with any of the measurements from signals from other occasions. Provided that the measurements are derived from known locations, a sufficient set of range measurements yields a position fix (fix). The range equation in 3D space is given by

In some local coordinate frames, the coordinate system is represented by (x)_i,y_i,z_i) The location of the transmitter is given and the unknown location of the mobile unit is given by (X, Y, Z). The three or more transmitters produce three or more range measurements that are used to calculate the bearing. The measurement also has a receiver time offset addition since the receiver time is not synchronized with the WAPS time.

R_i=r_i+cΔt

This equation is referred to as the "pseudo-range measurement equation". Note that because the timing of the transmitters is synchronous, the time offsets are common. The pseudoranges must be corrected for transmission timing correction values available from the data streams embedded in the transmissions from each transmitter. This delta time offset creates a new unknown parameter, and therefore a minimum of four measurements are used to solve for. Barometric altimeter measurements provide the information needed for solution as

Baro=(z_b-Z)。

One way to solve these non-linear simultaneous equations is to linearize the problem at any initial point and then iteratively find a correction to that initial position to iteratively arrive at a final solution.

This method uses an initial guess at the X, Y, Z solution, and thus uses the centroid of the transmitter as the following equation

Assuming that the final position solution is of the form

(X,Y,Z,Δt)=(X₀，Y₀,Z₀,Δt₀=0)+(dX,dY，dZ,dΔt)

Can be found in relation to (X, Y, Z, Δ t) = (X)₀,Y₀,Z₀,Δt₀) Extended geometric range in the Taylor (Taylor) series

Wherein the estimated range is calculated as

And the partial derivative is given by

In the present embodiment, four linear equations with four unknown values are shown. Additional range estimates will produce more rows in the matrix. The result is a set of equations below

The last row of the observation matrix represents the barometric altimeter measurement. The three 1 columns represent the same time offset across all three ranges. These equations are of the form Ax = b. Solution x = A^-1B. Note that without the barometer measurement, one more additional measurement would be added by an additional row similar to rows 1 to 3 of the matrix above. This additional measurement will enable the altitude of the receiver to be estimated. Note that when there are more measurements available than unknown values, then the solution will be based on the values from A₊=(ATA)^-1A^TPseudo-inverse of a given and is represented by x = a₊ ^-1b gives a least squares solution. When the quality of the measured values is not the same, the best way to solve the equation Ax = b in the least squares sense is to use a weight proportional to the SNR for the error from each equation. This yields a solution x = a₊ ^-1b, wherein A₊=(A^TWA)^-1A^TW is added. The diagonal weighting matrix W is formed of weights proportional to the noise variance of the measured values. The solutions to these equations produce delta correction values and delta time estimates for X, Y, Z such that

This completes the first iteration of the method. The initial guess is replaced with the updated position and time bias estimates and the algorithm continues until the delta parameter is below some threshold. A typical stopping point will be specified with a delta value below a certain threshold (e.g., 1 meter).

The linearized system of equations in GPS is solved using least squares and an initial guess about the user's location so that the algorithm converges to the end user location. Linearization is based on the basic assumption that the distance between the satellite and the user's position is greater than the distance between the user's position on earth and the guessed position. For the same set of equations operating in a terrestrial environment (with small geometries), the initial guess can be based on the centroid (as above), the point near the transmitter where the received signal is the strongest, or by a direct method that gives a closed form solution by means of a sequence of equations without iteration. When the initial guess is the centroid or a point close to the transmitter where the received signal is the strongest, the initial guess is improved using least squares. When the initial guess is obtained by a direct method giving a closed form solution by means of a sequence of equations without iteration, the initial solution itself is the final solution, and the least squares are used to improve the initial guess only when there are more measurements (and hence equations) than unknowns, where the expected errors in these measurements (which are obtained from parameters such as signal strength and altitude angle) are used to weight the individual measurements. Furthermore, if the sequence of measurements is to be processed in time, a Kalman (Kalman) filter may be fed with the solution obtained as above to obtain an optimal solution "trajectory".

Another approach to overcome the problem of linearization in terrestrial situations involves formulating a system of equations as a non-linear minimization problem (specifically, as a weighted non-linear least squares problem). In particular, the non-linear objective function to be minimized is defined as

Selecting a weight W_iAnd the measurement range R_iIs inversely proportional. The best estimate of the receiver location is obtained as the set of (X, Y, Z, Δ t) that minimizes the objective function. When barometer or other altitude aiding is available, then the objective function is modified to

A position solution based on this approach will be more stable and robust, especially in small geometry ground system configurations. In such a configuration, small changes in receiver coordinates significantly change the observation matrix and sometimes cause the linearization iterations to not converge. Convergence to a local minimum or divergence occurs more often due to residual bias in the measured values that affects the shape of the objective function such that there may be local minima. Residual bias may be quite common in indoor/urban canyon environments. The above non-linear formulation, in addition to overcoming the small geometry linearization problem, makes the position algorithm robust against measurement bias.

One way to minimize the function f to obtain the best X, Y, Z is to use a genetic algorithm (e.g., differential evolution) to find the global minimum of the function. Using such an algorithm enables the solution to avoid local minima that occur in small geometry terrestrial positioning when multipath offsets are present in the range measurements.

Whether linearized least squares or non-linear least squares are used to solve the pseudorange measurement equations, it is important to provide a quality metric along with the position estimate. The position quality metric should be a function of the pseudorange measurement equation residuals, the quality of the measurements, and the geometry of the signal tower relative to the estimated position. The pseudorange measurement residual for the ith signal tower measurement is given by

The average weighted rms pseudorange residuals are given by

According to H = (A)^TA)^-1A^TThe diagonal elements of (A) define HDOP, VDOP, PDOP as

VDOP=H(3,3)

The pseudo-range RMS (root mean square) error at a particular SNR is given by

Where f is typically a non-linear monotonically decreasing function of its argument. The function f can be derived analytically for a particular receiver configuration as a function of the signal BW and the receiver BW or, alternatively, obtained from simulations as a table mapping SNR to range error.

Defining a quality metric for a 2-D location as

Similarly, the quality metric for altitude and 3-D position is given by

the quality α is selected based on the desired confidence level, for example, a value of 3 would be used to obtain a 95% confidence, while a value of 1 would be used for a 68% confidence.

Another method of positioning using the WAPS system involves using a WAPS reference receiver in a differential scheme. As shown in the "differential wide area positioning system" and discussed in the context of timing synchronization, reference receiver measurements of frequency band time stamps can be used along with latitude, longitude, altitude of the WAPS signal towers and reference receivers to determine the timing δ between WAPS signal tower transmissions at a particular time stamp. Once the timing δ between the transmitters is known, the range equation can be reduced to again have a single common time offset. The WAPS receiver may then refrain from demodulating the WAPS data stream (e.g., extracting timing correction values from the data stream). The WAPS receiver measurements may be sent to a server where the position may then be calculated, or alternatively, the reference receiver measurements may be relayed to the WAPS receiver where the position may be calculated. It is assumed that the latitude, longitude and altitude of the WAPS signal tower are already known/available for use in the position calculation. In the case of WAPS data streams that are secure, the differencing system can avoid the need to extract data from the secure data stream for the purpose of obtaining timing correction values.

An alternative method of obtaining position location from a WAPS system uses RSSI fingerprinting (finger-printing technique). A database of WAPS signal tower transmit power/location and RSSI levels is built for a given target area based on training measurements in the area where positioning is desired. Note that the RSSI database may also be extended with angle of arrival (AOA) information to improve the solution. The WAPS receiver RSSI measurements (and possibly AOA measurements) are then used to consult the database to obtain a location estimate. An alternative method of using WAPS RSSI measurements would be to transform the measurements into range estimates using a propagation model (or a simple extrapolation/interpolation technique) and then determine the position using a three-multi-edge method (tri-correlation). Note that the RSSI measurements in these fingerprinting techniques may be replaced by any other measurement that can be transformed into a range.

An alternative method of calculating position using the WAPS infrastructure uses a blind method of obtaining position fixes from the WAPS system without prior knowledge of the WAPS signal tower location. In this approach, the approximate location of the WAPS signal tower is determined by field measurements (e.g., by measuring RSSI at GNSS-identified locations from many angles around the WAPS signal tower and then using a weighted average based on the RSSI at those locations to estimate the WAPS signal tower location). The location may then be determined using any of the RSSI fingerprinting methods (e.g., as described in the above paragraph).

The position can be computed offline using an alternative method of computing position using the WAPS infrastructure. The position calculation includes storing sample segments of the WAPS signal from the WAPS receiver (e.g., the stored data may be I data at low IF or IQ data at baseband), optionally along with an approximate position and a WAPS time tag. Note that enough samples are stored to enable signal acquisition. The samples are processed at a later time to search, acquire and compute the range to the WAPS signal tower. This approach may use offline data to look up beacon location and timing correction value information, which may be stored in a central database on the server. This offline position calculation method provides the ability to support WAPS positioning only at the cost of memory on the device. An additional advantage of this approach is that the time taken to store WAPS IQ data is very short, making it convenient for applications that need to mark positions quickly, but do not immediately need accurate positions. One possible application of this method may be for geotagging photos.

Another method of positioning uses carrier phase measurements in addition to the code phase measurements noted above. The carrier phase measurement can be written as:

φ_i(t₀)=r_i(t₀)+N_iλ+Δt

various techniques may be used to blur N integers in carrier phase measurements_iAnd (6) solving. Code phase measurements, measurements at multiple frequencies may be usedAnd/or other methods to solve for the ambiguity. Then, at time t_kThe carrier phase measurements at (a) may provide accurate tracking of position from an accurate initial position. The carrier phase measurements at future times may be written as

φ_i(t_k)=r_i(t_k)+N_iλ+Δt

As long as the carrier phase measurement has no cycle slip (i.e., the signal should be tracked by continuous phase lock), N_tNo change occurs and a new location can be calculated using least squares. Alternatively, these measurements may be used in a kalman filter to update the new position state. If phase lock is lost, a new integer ambiguity value needs to be calculated.

Another approach uses differential positioning with respect to a reference receiver as described above. Differential positioning may be performed using code or carrier measurements or a combination of both. As follows, the single-difference observations are calculated for the code and carrier phase by subtracting the measurements of the same signal tower from the reference receiver r and the receiver s

Note that any timing errors in the transmitters do not occur in these observations, thus enabling a position solution to be found even when the systems are not synchronized or not fully synchronized. In addition, since tropospheric delays may be correlated in a local region of a short baseline (e.g., the distance between the reference receiver r and the receiver s), any tropospheric delay errors in the measurements are close to cancelling out. The range and carrier measurements are transmitted from the reference receiver r to the receiver s using a communications channel for position calculation. Or alternatively, the receivers s and r need to transmit the range and carrier to the server for position calculation.

In any location solution method, the height of the receiver may be determined using placement on a topographical map or air pressure sensing. Using the arrangement on the map, the user's location may be limited to a certain terrain during trilateration based on the terrain database and the determined height of the user. The height of the user may also be limited to a certain height above the terrain. For example, the maximum altitude above the terrain may be limited based on the highest buildings in the area. This type of limitation may improve the quality of the height solution (e.g., by eliminating ambiguous solutions that are generated from time to time when range measurements of the bias are used).

Additionally, if an indoor architectural map is available, this information (along with associated restrictions on possible user locations) can be used to assist in location resolution. For example, physical constraints may be used to constrain the user motion model, thereby improving the quality of the tracking kalman position filter. Another use of the architectural drawings is to determine/estimate the quality of range measurements for a particular signal tower based on the physical environment from the signal tower to the indoor site. The better range quality estimate may be used to weight the position calculation to obtain a better position estimate.

When using a barometric pressure sensor, a calibrated barometric pressure sensor may be used to measure the pressure difference as the receiver terminal moves up or down in altitude. This is compared to calibrated or average values of pressure at different altitudes to determine the height of the receiver.

In calculating the position solution, "orphaned" measurements are eliminated using receiver integrity monitoring based on a check for consistency of the measurements when additional measurements are available that are greater than the minimum three measurements required for a two-dimensional position. The "orphan" measurement may be due to loss of timing synchronization at the transmitter or due to channel effects such as multipath.

Altimeter-based method for determining altitude (elevation)

The WAPS system of an embodiment includes an altimeter (pressure sensor) to assist in the determination of the altitude of the user. The only information available from the pressure sensor is the atmospheric pressure at the time and the measurement location. In order to convert this into an estimate of the sensor's altitude, a number of additional information is required. There is a standard formula relating pressure to altitude based on the weight of the column of air, as follows:

wherein z is₁And z₂Is two altitudes, P₁And P₂Is the pressure at these altitudes, and T is the temperature of the air (in K). R =287.052m²/Ks²Is the gas constant, g =9.80665m/s²Is the acceleration due to gravity. Note that this formula provides relative information for determining the altitude difference for the pressure difference. Usually in z₂The formula is used in the case of =0, whereby P₂Is sea level pressure. Since sea level air pressure varies significantly with weather conditions and with location, sea level pressure is required in addition to the temperature and pressure of the site whose altitude is to be determined. When applying T =15C and P =101325Pa standard atmospheric conditions, an increase in altitude of 1 meter was found to correspond to a pressure decrease of 12.01 Pa.

Therefore, to determine altitude with a resolution of 1m, sea level pressure must be known with an accuracy significantly finer than 36 Pa. It is also worth noting that since T is measured in units of absolute temperature scale (Kelvin), a temperature error of 3 ℃ (or K) corresponds approximately to an altitude error of 1%. This may become significant when determining altitudes significantly above sea level, and when attempting to solve for higher floors in a high-rise building. Therefore, in order to determine the altitude with a resolution of 1m, a pressure sensor with high accuracy and resolution is required. To fit mobile devices, these sensors should have low cost, low power and small size. Note that commercial weather-grade sensors do not provide this level of accuracy and resolution, and are not updated at the rate required to determine altitude.

The key to determining altitude to an accuracy of 1m is to have a system that provides sufficiently local and sufficiently accurate reference pressure information. Must be able to provide measurements of temperature close to unknown locations and close in distance and time to capture changing weather conditions; eventually, it must be accurate enough. Accordingly, the altitude determination system of an embodiment includes, but is not limited to, the following elements: a mobile sensor that determines pressure and temperature at an unknown location with sufficient accuracy; a reference sensor array that determines pressure and temperature at a known location with sufficient accuracy and sufficiently close to an unknown location; an interpolation-based estimation algorithm that inputs all reference sensor data, reference sensor locations, and other expansion information, and generates accurate reference pressure estimates at the locations of interest within the WAPS network; a communication link between the reference sensor and the motion sensor for providing the reference information in a sufficiently timely manner. Each of these elements is described in detail below.

Fig. 27 is a block diagram of a reference altitude pressure system, under an embodiment. Typically, a reference altitude pressure system or reference system includes a reference sensor array including at least one set of reference sensor units. Each set of reference sensor units comprises at least one reference sensor unit located at a known location. The system also includes a remote receiver that includes or is coupled to an atmospheric sensor that collects atmospheric data at a location of the remote receiver. A positioning application running on the processor is coupled to or is a component of the remote receiver. The positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from the reference sensor units of the reference sensor array. The positioning application calculates the altitude of the remote receiver using the reference pressure estimate.

More specifically, the reference altitude pressure system includes a mobile sensor that determines pressure and temperature at an unknown location with sufficient accuracy, and the mobile sensor is a component of or coupled to a remote receiver. The system includes a reference sensor array including at least one reference sensor unit that accurately determines pressure and temperature at a known location suitable for the location of the remote receiver. The reference sensor unit communicates with a remote receiver and/or an intermediate device (e.g., server, repeater, etc.) (not shown) to provide reference information. The system includes a positioning application that, in embodiments, is an interpolation-based estimation algorithm that inputs all of the reference sensor data, reference sensor locations, and other developed information, and produces a relatively accurate reference pressure estimate at the location of interest. The positioning application may be a component of the remote receiver, may reside on a remote server or other processing device, or may be distributed between the remote receiver and the remote processing device.

Fig. 28 is a block diagram of a WAPS integrated with a reference altitude pressure system, under an embodiment. As described herein, a WAPS includes a network of synchronized beacons, a receiver unit (and optionally with a location calculation engine) that acquires and tracks beacons and/or Global Positioning System (GPS) satellites, and a server that includes an index of signal towers, a charging interface, a dedicated encryption algorithm (and optionally a location calculation engine). The system operates in a licensed/unlicensed band of operation and transmits dedicated waveforms for positioning purposes and navigation purposes. The WAPS system may be used in conjunction with other positioning systems or sensor systems to provide a more accurate location solution. Note that the altitude of the remote receiver calculated using the reference pressure estimate may be used, either explicitly as an altitude estimate, or implicitly to assist in position calculation in an arbitrary position location system.

One example system integrates a reference altitude pressure system and a WAPS. Typically, the integrated system includes a network of terrestrial transmitters including transmitters that broadcast positioning signals including at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system includes a reference sensor array including at least one reference sensor unit located at a known location. The remote receiver includes or is coupled to an atmospheric sensor that collects atmospheric data at the location of the remote receiver. A positioning application running on the processor is coupled to or is a component of the remote receiver. The positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from a set of reference sensor units of the reference sensor array. The positioning application calculates a position of the remote receiver including an altitude using the reference pressure estimate and information derived from at least one of the positioning signals and satellite signals that are signals of a satellite-based positioning system.

More specifically, the integrated system includes a mobile sensor that determines pressure and temperature at an unknown location with sufficient accuracy. The motion sensor is part of or coupled to a remote receiver, but is not so limited. The system includes a reference sensor array including at least one reference sensor unit that accurately determines pressure and temperature at a known location suitable for the location of the remote receiver. The reference sensor unit communicates with a remote receiver and/or an intermediate device (e.g., server, repeater, etc.) (not shown) to provide reference information. One or more WAPS transmitters may be configured with the reference sensor unit and/or the reference sensor unit may be separately positioned at other known locations. The system includes a positioning application, which in an embodiment is an interpolation-based estimation algorithm that inputs all of the reference sensor data, reference sensor locations, and other developed information, and generates a reference pressure estimate at the location of interest. The positioning application may be a component of the remote receiver, may reside on a WAPS server or other processing device, or may be distributed between the remote receiver and the WAPS server.

As mentioned above, motion sensors should be able to determine pressure with a resolution and accuracy significantly finer than 36Pa, many pressure sensors have built-in temperature sensors to provide compensation for undesirable sensor performance, but these sensors cannot provide sufficiently accurate measurements of outside air temperature due to spontaneous heating effects. Even in cases where accurate sensors are not available on the market, sensors with sufficient resolution may be used for the purpose of altitude estimation at the floor level if they are available. The mobile sensor of an embodiment determines the reference pressure data at a resolution of approximately less than 36 pascals and the temperature data at a resolution of at least one of approximately equal to and less than 3 degrees celsius.

These sensors have inherent short-term and long-term stability problems that can be corrected by moderate filtering techniques such as averaging over several samples. Each sensor may also have an offset that is likely to change with temperature, for example, requiring calibration or compensation of the offset by a look-up table.

With sufficient calibration, these sensors should provide the required accuracy. Some sensors may also be sensitive to high rates of motion. Some heuristic rules may be used that limit the use of pressure information when high velocities or accelerations are identified. However, high speeds are rarely experienced in indoor environments. When traveling at high speeds, GPS position and map data will generally provide sufficient vertical position information.

It should also be noted that the sensor should be mounted in a manner that exposes the sensor to outside air (but no wind, airflow, or other air movement). Installation or positioning into the interior of a typical consumer product should produce acceptable results. The battery compartment and connectors provide an indirect path for outside air to reach the sensor while preventing any direct air movement. However, the waterproof device would require special provisions to provide access to the sensor from the outside.

The reference sensors will be deployed in a much smaller volume and at a dedicated site, so relatively better accuracy can be obtained in the reference system, enabling the mobile sensors to be allocated the most of the overall error budget. Existing markets for absolute pressure sensors, such as weather and aircraft altimeters, do not have the same high accuracy requirements as the application of the embodiments. In a reference application, embodiments use multiple sensors for redundancy and for improved accuracy by averaging their measurements. Additionally, the sensor may be packaged to limit the temperature range over which the sensor is exposed and optimally calibrate the sensor for that limited temperature range.

The reference system should average or otherwise filter the various measurements to improve accuracy using a time scale on the order of seconds to minutes. The height of the reference sensor should be measured to a 'centimeter' level accuracy; the outside air temperature should be continuously measured and recorded; the sensor should be exposed to the outside air to measure air pressure, but must not be subject to wind, air currents, or other significant air movement (baffles or other packaging may be used to direct air along paths other than directly to the sensor); the sensor should not be sealed in a waterproof housing as this may interfere with the measurement of external air pressure. The reference sensor of an embodiment determines the reference pressure data at a resolution of approximately less than 36 pascals and the temperature data at a resolution of at least one of approximately equal to and less than 3 degrees celsius.

Embodiments enable interpolation-based reference pressure estimation. Given the pressure and temperature measurements at each WAPS transmitter tower, as well as the tower location and other development information, embodiments predict sea level atmospheric pressure at a mobile subscriber location as a baseline value for the subscriber altitude estimate. Thus, an atmospheric pressure surface gradient model is generated, and the pressure measurements at each signal tower site are used as sample data for local correction of the model. Thus, the estimation algorithm calibrates comparable reference pressure accuracy at the user site as a direct measurement captured at the beacon tower.

A description of the formulation of this interpolation is described below. Within a WAPS network, given reference barometric pressure sensors at n transmitter towers, the equivalent sea level barometric pressure is estimated based on the reference sensor outputs. This is done in two steps, but is not limited thereto.

As a first step, a reference sensor height h above sea level at a transmitter signal tower i is given_i(in meters) and the pressure p read from the reference sensor_i(in pascals) and temperature T_i(in absolute temperature scale), the calculation has a latitude x using the following formula_iAnd longitude y_iEquivalent sea level atmospheric pressure P at a location (in degrees)_i(in pascals):

where g is the gravitational acceleration constant and R is the specific gas constant of air. As a second step, the equivalent sea level atmospheric pressure at all n transmitter sites of the WAPS network is calculated, and the latitude x of the user is obtained using the WAPS₀And longitude y₀After the information, the user location P is estimated using the following formula₀Equivalent sea level pressure of (c):

wherein, W_i=W_i(x₀,y₀,x_i,y_i) Is a weighted function that depends on both the user location and the reference location i location.

The communication link of an embodiment provides information used by the mobile sensor. Embodiments broadcast pressure updates every few seconds to minutes, but are not so limited.

If the reference system rarely broadcasts reference information, the mobile unit at least one of: in the event that information is needed before the next broadcast, continuously monitoring the broadcast to receive and store the last information; waiting for the next broadcast before calculating the new altitude; the reference system is "pulled" or queried for up-to-date information when needed. The pull method of an embodiment minimizes system bandwidth rather than having the reference system broadcast information. However, pull uses two-way communication between the reference system and the mobile terminal, and since multiple reference sites will be used for any mobile calculation, it requires the mobile terminal to determine which reference site it should interrogate. A good compromise to minimize monitoring by the mobile terminal while maintaining low latency is to have the reference system broadcast its data more frequently than it takes to update the measurements.

Embodiments include two possible approaches to information content. The first method causes the mobile terminal to perform all calculations, in which case the information sent by the reference (reference) includes, but is not limited to, the following: a reference location (latitude and longitude) with one meter accuracy; height of the reference sensor with accuracy of 0.1-0.2 m; the measured temperature of the air at the reference site (after some filtering); measured pressure of air at a reference site with 1Pa accuracy (after filtering, sensor temperature compensation, and any other local calibration such as offset); and a measure of confidence.

Alternatively, the reference site may use its temperature and pressure measurements to calculate the equivalent sea level pressure. If this method is used, the list of information to be broadcast includes, but is not limited to, the following: a reference location (latitude and longitude) with one meter accuracy; height of the reference sensor with accuracy of 0.1-0.2 m; calculated equivalent sea level pressure at the reference site (with 1Pa accuracy); a measure of confidence.

Embodiments also reduce the bits of the transmitted data, but broadcast each relative to some known constant. For example, the reference location is relatively close to the mobile location, so only the fractional degrees of latitude and longitude (fractional degree) may be sent, leaving the integer part to be employed. Similarly, although air pressure is typically at 10⁵In pascal order, but the air pressure changes only a few thousand Pa from the standard atmospheric pressure. Thus, embodiments broadcast an offset from standard atmospheric pressure to reduce bandwidth when broadcasting absolute pressure.

The latitude and longitude obtained from GPS or similar systems is not particularly useful in urban applications. Instead, a database mapping latitude and longitude to street addresses is required. Altitude has similar limitations on vertical latitude. A useful parameter is on which floor the person is. If there is access to a database of ground elevations and heights of each floor in the building, this can be accurately determined from elevation information. For buildings down to approximately 3 floors, it may be sufficient to know the ground level from a map or similar database and estimate the floor height. For higher buildings, more accurate information about the floor level will be required.

This presents an opportunity to implement intelligent learning algorithms. For example, it may be assumed that a cellular phone will be carried between 1m and 2m from the floor. Thus, the system of an embodiment may accumulate the altitude of many cell phones in a building, where the expected data is aggregated around 1.5 meters from each floor. With sufficient data, confidence can be established as to the height of each floor in the building. Thus, the database can be learned and refined over time. Such algorithms become more complex in buildings with ramps or sandwiches between floors, but still can generate useful data for most buildings.

The sensor offset and potentially other parameters may be calibrated at the time of manufacture. This should be possible by cycling the sensor through a range of temperatures and pressures using known good sensors that provide baseline information. It is likely that these calibration parameters will drift slowly with age. Thus, embodiments use an algorithm that gradually updates calibration values over time (e.g., when the sensor is fixed at a known height, the algorithm identifies and updates the calibration table under these conditions).

In addition to general applications for determining the location of a person, embodiments may also include specialized applications that use more accurate relative altitude information, without requiring absolute altitude information. For example, finding a firefighter knocked down in a building requires precise knowledge of the position of the knocked down person relative to the rescuer, but the absolute position is not as important. Additional accuracy in the relative positioning would be possible by having an extra manual step at the start of the application. For example, all firefighters can initialize their tracker at a known location, such as a building entrance, before they enter. Even if the absolute altitude is not accurate and cannot fully compensate for weather-related pressure changes, their position relative to the point and thus to each other can be determined quite accurately within a certain period of time. Similarly, by having the user press a button at a known point in the mall, a shopping-related application may be implemented that requires a higher precision than that obtainable from absolute measurements. Their position relative to the point can then be determined fairly accurately over a certain period of time.

Alternatively, a mobile beacon may be utilized as a local reference, providing greater accuracy at a particular location. For example, a shopping mall may have its own reference sensor to provide greater accuracy within the mall. Similarly, fire trucks may be equipped with reference sensors to provide local reference information in a fire scenario.

A problem with low cost pressure sensors is that they have an offset from the correct reading. Experiments have shown that this shift is fairly stable on a time scale of weeks to months. However, it is likely that this offset will drift slowly over time over a period of many months to years. Although this offset is measured directly and compensated for at the time of manufacture, it is not possible that the product life compensation remains accurate. Therefore, means for re-calibration in the field are required.

If the sensor of an embodiment is at a known altitude and the barometric pressure is known, the sensor of an embodiment may be recalibrated. Embodiments recognize the actual situation in which an altitude sensor would be known to be. For example, if the sensor is in a GPS-capable device and is receiving GPS satellites at high signal strength, the GPS-derived altitude should be reasonably accurate. Under good signal conditions, accumulating the deviation from GPS altitude over time can provide an estimate of the correction value required for sensor calibration.

Similarly, the sensor system may learn the habits of the user and use this information to later correct the calibration. For example, if a user has placed their phone in a place all the way through the night, the sensor may start tracking the altitude at that place at a particular time, such as late at night. Initially, these values will be accumulated and stored as the true altitude of the site. After a few months, when the sensor determines that it is in the same location at the same time of the night, it can start tracking deviations from determining the true altitude earlier. These deviations can then be accumulated to slowly generate a correction value for the calibration. Because these methods also use knowledge of the current atmospheric pressure, they use reference pressure measurements provided by the WAPS network.

The standard process of determining altitude from pressure readings involves converting measurements at a reference site to an equivalent sea level pressure, which is then used to determine the altitude of the unknown pressure sensor. The standard formula is:

note that, since it is conventionally used asPositive movement away from the earth's surface measures altitude, so a negative sign is added. In addition, since this is a natural logarithm, the logarithm is corrected to 'ln'. The formula relates the height z above sea level to the atmospheric temperature (T) and pressure (P) at that point and the sea level air pressure (P) below that point₀) And (4) correlating.

An additional problem with applying this formula is that the height is directly proportional to the temperature (an inaccurately known measurement quantity). This means that a temperature error of 1% will result in a height error of 1%. This will not be a significant problem when used near sea level. However, when applying this formula in high buildings, particularly in areas of higher altitude such as Denver (Denver), a height error of 1% may be very significant when trying to solve for floor level altitude. For example, the altitude of denver is approximately 1608 m. Thus, a temperature error of 1% will result in an altitude error of 16m above sea level. This is almost a 5-story floor.

One way to avoid this sensitivity to temperature accuracy is to recognize that the above formula is actually a relative formula. That is, the formula can be generalized as:

wherein z is₁And z₂Is any two altitudes, P₁And P₂Is the pressure at these altitudes. Will z₂Is set to 0, whereby P₂To sea level pressure (this is merely a matter of convention).

Instead of using sea level as a reference point, any convenient altitude may be used. For example, the average altitude of a city would be reasonable, or the average altitude of a reference sensor used to collect pressure data would be feasible. The effect of temperature error will be negligible as long as a reference altitude is used that keeps the altitude difference small. The only requirement is that all devices contained in the system know what reference altitude is being used.

There is a point above the ground's altitude (z) and the atmospheric temperature (T) and pressure (P) of that point and the sea level air pressure (P) below that point₀) The relevant standard formula of the process is shown,

the formula assumes that there is a column of air at a constant temperature between sea level and the point of interest. Thus, the sea level pressure used is fictional, not necessarily the true pressure of the sea level, as the point of interest may not be near the true sea level.

The standard process of determining the altitude of an object is a two-step process. First by measuring the temperature and pressure at a point of known altitude, and then reversing the equation to target P₀And solving to determine the sea level pressure. Next, the temperature and pressure at a point of unknown altitude are measured and the formula is applied to determine the unknown altitude.

Implicit in this process is the assumption that the only parameter of interest is the height of other objects above the same horizontal location, as is typical for aircraft approaching an airport, using measurements at the airport for reference. Generally, people who are interested in height determination for other purposes extend this concept to determine heights that are generally near, but not directly above, the reference location. This extension assumes that sea level pressure does not vary between nearby points of interest and the reference point.

Therefore, there are three assumptions in this process. The first assumption is that the temperature is constant from the reference point to the virtual sea level point below it. The second assumption is that the temperature is constant from the point of interest to the virtual sea level point below it. The third assumption is that the sea level pressure is the same at the reference site and the point of interest. However, since sea level pressure depends on temperature, assuming that sea level pressure is the same at two locations, it implies that the temperature is the same at both locations. Thus, if different temperatures are measured at the reference site and the point of interest, one of these assumptions is violated. Measurements have shown that even over distances of several kilometers, there are temperature and pressure differences that can be significant for altitude determination.

The assumption that a constant temperature varies with altitude at a given site is part of the equilibrium model for the atmosphere and may be necessary. The only options would be a fully dynamic model of the atmosphere including the effects of wind, surface heating, convection and turbulence. Atmospheric data show that, at least on a large distance scale, the constant temperature model is a very good approximation at altitudes below 1 km. At higher altitudes, a linear rate of decrease is often applied.

The embodiment relaxes the assumption that sea level pressure is constant between the reference location and the point of interest. The first method of the embodiment takes the sea level pressure at the reference site as determined above, but further applies the ideal gas law to convert this to the sea level pressure at the standard temperature. Then, assume that the sea level pressure at this standard temperature will be the same at the point of interest. The temperature at the new site will then be used, converting this to sea level pressure for that site, and then applying the above formula to determine altitude.

A second method of an embodiment uses a network of reference sites to determine in real time the change in equivalent sea level pressure relative to a horizontal site. These multiple measurements are then combined to determine the best estimate of sea level pressure at the point of interest. There are at least two possible ways to determine the best estimate: a weighted average method, wherein the weight is a function of the horizontal distance from a particular reference point to the point of interest; a least squares fit to create a second order surface that best fits the calculated sea level pressure at the reference location, which can then be used to interpolate an estimate of the sea level pressure at the point of interest.

It is also possible to combine the two methods described above. That is, at each reference location, the sea level pressure at the standard temperature is determined and the data is combined using one of the techniques above to generate the best estimate of the sea level pressure at the standard temperature at the point of interest.

In addition, when using altimeters, embodiments identify sudden movements of pressure, such as air conditioning changing state (e.g., on, etc.) or window opening in an automobile, by using a hardware or software filter that applies level data to continuously operate on location and altimeter data.

Furthermore, an anemometer may be used at the beacon to determine the direction of wind flow, which is believed to be indicative of the atmospheric pressure gradient. An anemometer may be used with a compass to determine the precise direction and level of wind flow (which may then be used to correct and/or filter for changes in the user's sensors).

Each floor height of a given building may be determined by various methods including, but not limited to, a user walking through the stairs in the building and collecting information for each floor, ramp, etc. In addition, an electronic map may also be used to determine the relative altitude of each floor.

When the altitude is estimated based on the WAPS or altimeter, information such as the terrain, the altitude of the building, the altitude of the surrounding building, etc. may be used to limit the altitude solution.

Once the average pressure is known at a given site along with historical reference pressure data collected from the reference sensors over a long period of time (days, months, years), the altitude may be predictively determined (without calibration or user input) based on the pressure at that site.

In one embodiment, the height of the user may be calculated on a remote server by using data from the user's sensors and combining it with data from the reference sensors. In this approach, other information, such as building information, crowd source information, etc., may also be used to determine the precise altitude of the user.

This information may be used to determine the height of an unknown user in the event that the user is close to another user whose height is known.

In one embodiment of the network, the reference sensor is not necessarily co-located with the WAPS beacon. A finer or coarser grid of independent sensors with data connections to the server may be used for reference pressure measurements. The central server may send the reference pressure information to the mobile terminal or may indicate to the transmitter that data needs to be sent to the mobile terminal as part of the WAPS data stream.

In another embodiment, the WAPS system uses additional simplified beacons (supplemental beacons) that provide additional sensor information such as, for example, pressure, temperature in a smaller area of a building. The transmission may or may not be synchronized with the master WAPS timing beacon. In addition, the supplemental beacons may upload sensor data to a central server, disseminate it from the central server to the mobile units, or may transmit data through a predefined set of PRN codes that are demodulated by the WAPS mobile receiver.

The reference pressure network may be optimized based on the accuracy requirements and historical pressure change data for a given local area. For example, in the case where very accurate measurements have to be made, reference sensors may be deployed in the building or mall.

The WAPS beacon network, together with the reference pressure data, forms a closed network of accurate pressure and temperature measurements with very short time intervals that other applications, such as geodetic surveying, can utilize.

The rate of change of pressure combined with data from other sensors can be used to determine vertical velocity, which can then be used to determine whether a user is moving through the elevator. This may be very useful in emergency situations and/or tracking applications.

In the case of sensors having a lower resolution than that required to estimate floor height, averaging pressure measurements over time may be used to obtain user height based on baseline data under static conditions.

Hybrid location and information exchange with other systems

The system of an embodiment may be combined with any 'signal of opportunity' to provide positioning. Examples of signals of opportunity include, but are not limited to, one or more of the following: a GPS receiver; galileo (Galileo); glonass (Glonass); an analog or digital TV signal; signals from systems such as MediaFLO, Wi-Fi, etc.; an FM signal; WiMax; cellular (UMTS, LTE, CDMA, GSM, etc.); bluetooth, and LORAN and e-LORAN receivers.

Regardless of the signal type, the signals of opportunity provide a range measurement or a representation of a range measurement (proxy) such as signal strength. The representatives of the ranges are weighted and combined appropriately to get an estimate of the location. The weighting may use the signal-to-noise ratio (SNR) of the received signal, or alternatively a metric defining the environment of the receiver (e.g., learning urban, suburban, rural environment from assistance data, learning whether the receiver is indoors or outdoors based on input from an application). This is typically done in those environments where the system of an embodiment is not available or where signal coverage is limited. When using SNR for weighting for a particular measurement, the weights may simply be the inverse of the SNR (or any other function that provides lower weights to signals with lower SNR) to enable the best combination of WAPS measurements and other system measurements to obtain the position. The final positioning solution may be calculated by taking range measurements from additional signal sources and combining with WAPS range measurements and deriving a position solution for latitude, longitude and altitude, or by taking position measurements from additional sources/devices and position measurements from the WAPS system and using a combination of these location measurements to provide an optimized location solution based on position quality metrics from different systems. Various configurations for obtaining a hybrid solution using WAPS measurement values/WAPS position estimation values are shown in fig. 29, 30, and 31. Any of the architectures described below may be selected for use depending on the hardware and software partitioning of the system.

FIG. 29 is a block diagram of hybrid position estimation using range measurements from various systems, under an embodiment. Range measurements from GNSS and other positioning systems (along with associated range quality metrics) are used and combined in a single best position solution by a hybrid position engine. This architecture is optimal in using the available data to get the best position estimate from them.

Fig. 30 is a block diagram of hybrid position estimation using position estimates from various systems, under an embodiment. Separate position estimates from different systems are used along with the position quality to select the one with the best quality. This architecture is most easily implemented and integrated since the different positioning systems are well isolated.

FIG. 31 is a block diagram of hybrid position estimation using a combination of range and position estimates from various systems, under an embodiment. For example, the position estimate from the WLAN positioning system may be compared to the position estimate in the range measurements from the GNSS and WAPS systems to arrive at the best solution.

Inertial Navigation Sensors (INS) such as accelerometers and gyroscopes, magnetic sensors such as electronic compasses, pressure sensors such as altimeters, may be used to provide location assistance information (referred to as loose coupling) or raw sensor measurements (referred to as tight coupling) to the WAPS system for use in tracking mode.

An accelerometer may be used in the receiver of an embodiment to determine the frequency with which to update the location report of the server. A combination of a position solution and a sequence of accelerometer measurements may be used to detect static position, constant velocity, and/or other movements. This movement data or information may then be used to determine the frequency of the update, such that, for example, when there is uneven motion, the frequency of the update may be set to a relatively high frequency, while when the receiver is at a constant speed or stationary for a predetermined period of time, the frequency of the update is reduced to conserve power.

The sensor or position measurements may be combined into a position solution in a position filter, such as a kalman filter. Two types of tightly coupled architectures are shown in fig. 32 and 33, where sensor measurements are combined with GNSS and WAPS measurements in the WAPS hybrid location engine. FIG. 32 is a flow chart of determining a hybrid position solution under an embodiment where position/velocity estimates from the WAPS/GNSS system are fed back to help calibrate the drift bias of the sensor from time to time when GNSS/WAPS position and/or velocity estimates are of good quality. This architecture simplifies the algorithm formulation by partitioning the sensor calibration and position calculation portions of the algorithm. However, a disadvantage of this approach is the complexity of deciding when it is a good time to recalibrate the sensor using the WAPS/GNSS estimate.

FIG. 33 is a flow chart of determining a hybrid position solution under an embodiment where sensor parameters (e.g., bias, scale, and drift) are estimated as part of position/velocity calculations in GNSS and/or WAPS units without explicit feedback. For example, sensor parameters may be included as part of a state vector of a Kalman filter used to track the position/velocity of the receiver. This architecture provides the best solution because the information is used in one synthesis filter to update both the position and sensor parameters.

The loose coupling is shown in fig. 34 and 35, where the selection unit selects between position estimates from the GNSS engine and the WAPS engine. Note that the selection unit may be part of the WAPS or GNSS location unit. FIG. 34 is a flow chart of determining a hybrid position solution, where sensor calibration is separated from individual position calculation units, under an embodiment. FIG. 35 is a flow diagram of determining a hybrid position solution under an embodiment in which sensor parameter estimation is performed as part of the state of the individual position calculation units.

Since the option is to use information from only one system, the loose coupling method is generally inferior to the tight coupling method. In either the loose coupling or tight coupling methods, the method of using the range together with the raw sensor measurements to determine the position and sensor parameters in an optimal filter is better than when calculating the sensor parameters and position alone. As a result, the preferred approach from a performance perspective is a tightly coupled system that implies estimation of sensor parameters. However, one or more of these methods may be readily implemented in terms of hardware/software platform partitioning, and may be selected for this reason.

Information may also be exchanged between the WAPS system and other transceiver systems on the same platform (e.g., cell phone, laptop, PND). The transceiver system may be, for example, a bluetooth transceiver, a WLAN transceiver, an FM receiver/transmitter, a digital or analog TV system, MediaFLO, a satellite communication system such as XM radio/Iridium, a cellular modem transceiver such as GSM/UMTS/cdma2000 lx/EVDO or WiMax). Fig. 36 illustrates the exchange of information between the WAPS and other systems in the case of an embodiment. The exchange of information between systems can improve the performance of any system. Because the WAPS system time is aligned with GPS time, the WAPS system can provide good quality timing and frequency estimates to any other system. Time and frequency estimates in a WAPS system may reduce the WAPS acquisition search space for codes and frequencies. In addition, the WAPS system may provide location information to other transceiver systems. Similarly, if other systems have available location information (e.g., altitude or partial position of a 2-D position or full position such as a 3-D position or raw range/pseudo range/range difference), the location information may be provided to the WAPS system with or without a location quality metric. Range/pseudo-range data should be provided along with the location of the transmitter (or other means for calculating the range from the transmitter location to any receiver location) to enable the use of the range information in the hybrid solution. The range difference corresponding to the two transmitters should be provided together with the locations of the two transmitters. The WAPS system will use this information to assist its location solution. Alternatively, the location information may be provided in the form of a range (or pseudo range) from a known transmitter location to a receiver device. These ranges (or pseudo ranges) will be combined with the WAPS ranges by a positioning algorithm to calculate the hybrid position.

Examples of specific systems and information that may be exchanged between them are shown in fig. 37, 38 and 39.

Fig. 37 is a block diagram illustrating the exchange of location, frequency and time estimates between an FM receiver and a WAPS receiver, under an embodiment. The FM receiver may be provided with a location estimate from the WAPS system. The location estimate may then be used, for example, to automatically determine active FM radio stations in the local area. The FM signal may also comprise an RDS (radio data service) transmission. If the location of the FM station is contained in an RDS/RBDS data stream (e.g., a Location and Navigation (LN) feature that provides data about the transmitter site, gives city and state names, and provides DGPS navigation data), this information can be used to provide the location of the auxiliary WAPS receiver. The frequency estimate from the WAPS system can be readily used to reduce FM receiver tuning time for a particular station. In the other direction, the frequency quality of the estimated value in the FM receiver is based on the FM radio station transmission quality. The time estimate in the WAPS system is based on GPS time and can be passed to the FM receiver to assist in timing alignment. Clock Time (CT) characteristics of RDS/RBDS transmissions may be used to determine timing relative to the RDS data stream, and the CT characteristics may be passed to the WAPS receiver.

Fig. 38 is a block diagram illustrating the exchange of location, time, and frequency estimates between a WLAN/BT transceiver and a WAPS receiver, under an embodiment. Typically, these WLAN/BT transceivers do not have accurate frequency estimates, and as a result, the frequency estimates will be rather coarse, and therefore the transfer of such estimates from the WLAN/BT transceiver to the WAPS receiver may have limited values. In the opposite direction, the WAPS frequency estimate may reduce the time it takes for frequency acquisition on the WLAN system. Timing information, e.g., extracted from timestamps on wireless LAN AP (access point) beacons, may be passed to the WAPS system to assist with WAPS acquisition. Note that some reference of WLAN timing relative to GPS time is needed to make this useful for the WAPS system. Similarly, if the WLAN/BT system has a location estimate available (e.g., altitude or partial position of a 2-D position or full position such as a 3-D position or raw range/pseudo-range), the location information may be provided to the WAPS system with or without a location quality metric. The WLAN position estimate may simply be the geographic location of the serving AP or other nearby "audible" APs. The WLAN position estimate may also be partial, such as an altitude estimate based on the floor of the problematic AP. The WLAN location information may also be a range estimate to a known transmitter AP location (e.g., the WLAN system may use a Round Trip Time (Round Trip Time) measurement to determine a range estimate) or a range difference estimate between two transmitting APs.

Fig. 39 is a block diagram illustrating the exchange of location, time, and frequency estimates between a cellular transceiver and a WAPS receiver, under an embodiment. The WAPS system may be provided with location estimates (partial, full or raw range/range differences) from the cellular system (e.g., from TDOA, AFLT or other similar cellular signal FL or RL based positioning methods) that the WAPS system will use to obtain better position estimates. The WAPS system may be provided with frequency estimates from the frequency tracking loop of the cellular modem to reduce the frequency search space, thereby improving the WAPS acquisition time (i.e., TTFF). The WAPS system may also be provided with time estimates from the cellular system to reduce the code search space or to assist in aligning bits and frames. For example, a system synchronized to GPS time, such as cdma2000/lx EVDO, may provide a good estimate of time for a WAPS system, while an asynchronous (transmission not accurately synchronized to a time scale, such as GPS) cellular system, such as GSM/GPRS/EGPRS/UMTS, may provide a coarse estimate of time.

Since the WAPS system time is aligned with GPS time, the WAPS system can provide good quality timing and frequency estimates to any other system, even if not on the same platform. For example, the WAPS system may be used to provide timing information to the pico/femto cell BTS via a periodic hardware signal such as pps (pulses per second) aligned with the second boundary of the GPS or a single pulse signal with associated GPS time.

As described above, the spectrum used by the WAPS system of an embodiment may include licensed or unlicensed frequency bands or frequencies. Alternatively, WAPS systems may use "white space" spectrum. The white space spectrum is defined as any spectrum in which the WAPS system senses or determines that it is free in a local area (not limited to TV white space) and transmits a location beacon in that spectrum. The transmitter of an embodiment may use spectrum sensing techniques to detect unused spectrum and/or transmit geographic locations (which may be readily obtained from a GPS timing receiver) to a central database of adjusted spectrum. The receiver may include spectrum sensing technology to listen for these beacons, or in another embodiment, the receiver may be informed of the frequency to which it is tuned using the communication medium. The WAPS system may accommodate dynamic white space availability or allocation (in cases where the transmitter is required to broadcast its geographical location to the central database, and then the central database allocates spectrum for transmission for the duration it needs to transmit and/or allocates the duration it needs to transmit). The WAPS system may broadcast continuously in the spectrum, as controlled by the central regulatory service for the spectrum, or may share the spectrum with other systems. The cut-rate and data rate of WAPS system components may be dynamically modified to match the accuracy requirements and/or signal power and bandwidth availability at any given time. The system parameter may be sensed by the receiver or may be transmitted to the receiver over a communication medium. The transmitters may form a local network or, in the case of a spectrum available in a wider geographical area, a continuous network.

The transmitter of an embodiment may also co-exist with other networks on the same transmission system in a time-shared manner. For example, the same spectrum may be used in a time-shared manner between a venue and an intelligent grid application. The transmitter is a broadcast transmitter using the maximum available power level, which can dynamically adjust its power level based on spectrum sensing or as requested by a central adjustment server. The receiver may utilize spectrum sensing or may transmit system parameters and the number of awakenings at that time to the receiver over a communication medium (which may also be a white space spectrum).

Based on spectrum availability, the WAPS system of an embodiment may use one channel of TV white space (6MHz bandwidth), or if multiple channels are available, multiple frequency bands to obtain better demultiplexing. If neighboring channels are available, channel bonding (e.g., combining neighboring channels) may be used. Increased bandwidth may be used to obtain better demultiplexing, higher cut rates with higher accuracy, etc. Optionally, the available bandwidth may be used under FDMA to help solve near-far problems and/or demultiplexing.

White space transmission/reception of WAPS waveforms in two or more white space bands may enable better and faster integer ambiguities to be obtained for WAPS carrier-phase measurements. This would enable relatively high accuracy (<1 wavelength level) single point positioning using WAPS.

It is also possible to use the white spatial bandwidth as a communication channel in the WAPS (in the case of using a reference receiver) between the reference receiver at the survey site and the receiver to find the location.

When the WAPS system in the licensed band is available in a wide area network, a white space based local network of signal towers can be used to extend the location accuracy of the WAPS receiver. The receiver can be designed to listen to both frequencies simultaneously or to switch between the licensed and white space bands and tune to the appropriate frequency.

White space bands may also be used to send assistance information to WAPS, GPS, or AGPS systems for location assistance and other assistance information like clock bias, satellite ephemeris, etc.

Where multiple frequencies are available with band separation, the WAPS can be designed to take advantage of the diversity of frequencies to provide better multipath performance.

Correlator implementation

In any CDMA receiver (or a receiver using a pseudo-random code as part of the transmitted bit stream), correlation of the received signal with its PRN code is essential. The more parallel correlations that can be performed, the faster the channel acquisition time. A brute force implementation of a parallel complex correlator architecture for a signal oversampled at 2x the input signal using a maximal length sequence of length 1023 is shown in fig. 40. The even and odd samples correspond to 2x oversampled data. The shift register is shifted at the rate of 'clk'. The PRN generator generates a reference PRN and is shifted at the rate of clk/2. The correlation sum for each cycle is calculated using the following equation

Where x [ n ] is the composite input, gcref [ k ] is the PRN reference waveform, and corrsum [ n ] is the composite output from the correlator. FIG. 37 shows an optimization of even and odd samples sharing the same multiplier and adder tree

The implementation as shown above requires 2046 x 2x n input bit flip-flops for the shift register, 1023 1xn input multipliers and an adder that sums 1023 products. As an example, if the input bit width is a 2-bit sample, 1023 1 × 2 multipliers would be needed and these 1023 multiplications would have to be summed over one clock cycle. This can be a cumbersome implementation in terms of area, timing and power of the hardware. In particular, in FPGA implementations, given limited resources, a brute force implementation of multiplier and adder structures may not be possible.

Embodiments include novel approaches to this implementation that utilize structures available in the FPGA process state. Modern FPGAs include several Configurable Logic Blocks (CLBs) that implement logic and storage elements. The look-up table forming an essential part of the CLB can also be reprogrammed as a shift register in which serial shifting is performed, but with parallel random access to the storage elements. Such an implementation can also be used in an ASIC implementation as a computationally-related efficient method and as an easy migration path from FPGAs (for prototyping) to ASICs (for mass production).

Turning to the shift register implementation, a particular FPGA has shift register cells mapped onto CLBs. Some FPGAs have 16-bit shift registers and some have 32-bit shift register mapping. FIG. 41 shows a 32-bit shift register implementation derived from two 16-bit shift register primitives with parallel random access read capability. In this example implementation, a 16-bit shift register set primitive is used to build a 32-bit shift register. 32 such 32-bit shift registers are arranged in series in a column to form a 1024-bit shift register. As shown in fig. 42, the shift operation is performed at the 'clk' rate, and the readout operation is performed at 32 times the clock rate.

The adder tree may also be complex to implement a 1023 n bit adder. In the case of a particular FPGA, a 48-bit DSP tile may be used that may be used as a 1023 × n bit sequence adder. The hardware structure of this implementation is shown in fig. 43. The 32 values from the 32 shift registers are split into 4 sets of 8 additions. In this example, a 2-bit input is used. Each adder # 8 produces a 10-bit output, which is then aligned in groups of 12 bits in a 48-bit adder. Consider the growing space for sums. After 32 cycles, a 1024 bit sum is obtained by adding 4 sets of 12-bit adders to one 14-bit sum.

Encryption and security

The overhead information in the system of an embodiment may be encrypted using an encryption algorithm. This enables the user to use the system and charge the user for the use of the system and provides a means of controlling the security of the information. The key may be applied to decrypt the signal. The key may be obtained using a PC, wireless network, hardware dongle, or burned into the non-volatile memory of the device in a manner that is inaccessible to any undesirable source.

The encryption of an embodiment provides both data security and authentication. The key components that use encryption protection are transmitter, receiver and server communications. Transmitter authentication involves explicitly identifying the transmitter so that a malicious transmitter can be resisted. Receiver authentication enables only trusted receivers to use the transmitted information. Receiver authorization is such that only authorized receivers (trusted receivers) should be allowed to operate. Server communications are encrypted so that communications between the receiver and the server and between the transmitter and the server must be secure. User data protection is also encrypted because the location tracking user database needs to be protected from unauthorized access.

The encryption method of the embodiment can be roughly classified into two types: symmetric key cryptography and asymmetric key cryptography. Symmetric key encryption provides both authentication and encryption, while asymmetric key encryption provides authentication of the owner of the private key, since the public key is available to anyone. Symmetric key encryption of data is an order of magnitude faster given similar resources. 3DES and AES are examples of symmetric key cryptography. A combination of the two approaches is used as part of the cryptographic architecture of an embodiment.

The over-the-air (OTA) broadcast message may comprise a general broadcast message or a system message. The general broadcast message contains data specific to each transmitter, such as location information, transmitter timing counts, and other relevant information that assists the receiver in determining the location of the receiver. System messages are used to construct encryption keys, to validate/invalidate receivers or to target one-way private information exchange to a specific group of receivers.

Common formats of messages for embodiments include: message type (parity/ECC protection); encrypting the message; and encrypting the message ECC. After encrypting the message, the ECC of the encrypted message is calculated.

OTA broadcasts comprise frames that are transmitted periodically, possibly every second. Depending on the channel data rate, the message may be split (fragmented) over multiple frames. Each frame includes a frame type and frame data. The frame type (parity protection) indicates whether this is the first frame of a message, or whether it is a consecutive frame; it may also indicate low level format frames that may be used for other purposes. The frame data is essentially a segmented message or a low level data frame.

The OTA system message can be encrypted by a session key or by a transmitter's private key based on the system message type. As described herein, OTA normal broadcast messages are encrypted using a symmetric key algorithm with a negotiated session key for both the transmitter and receiver. This provides mutual authentication, i.e. the receiver can authenticate the transmitter and only the authenticated receiver can decode the OTA broadcast. The session key is known to all transmitters and receivers and it changes periodically. The key change message is encrypted using several past session keys, which enables a receiver that is not active for a certain period of time to synchronize to the current session key.

The OTA broadcast also includes periodic system messages encrypted by the transmitter's private key. The receiver can use the associated public key to unambiguously distinguish the authenticity of the transmitter. In case the session key is compromised, this mechanism ensures that no unauthorized transmission can be achieved.

Fig. 44 is a block diagram of session key setting under an embodiment. Each receiver is provided with a unique device ID and a device specific key. Fig. 45 is a flow diagram of encryption, under an embodiment. The WAPS system data server maintains a database of device ID/device specific key pairs. Receiver initialization between the receiver and the WAPS data server is facilitated using a receiver type specific data connection (GPRS/USB/modem, etc.). After the device identifies itself with the device ID, the connection is encrypted using the device specific key. During this initialization, the current session key, the transmitter public key and the license period (i.e., the duration for which the receiver is authorized) are exchanged. Receiver initialization may occur when the receiver loses the current session key (initial power up) or in the event that its session key loses synchronization (extended shutdown). The session key is periodically updated and the new key used for updating is encrypted using the previous N keys.

The OTA data rate may not be sufficient for the only mechanism used to authorize the receiver. However, the system message protocol of an embodiment supports receiver authorization based on device ID specificity and device ID range.

Session key leakage requires all receivers to re-initialize. Therefore, the session key storage in the device should be tamper-resistant. Session keys stored outside the encryption boundaries of the device (i.e., any kind of attached storage) are encrypted using the device's security key.

The transmitter cannot be disguised using the compromised session key because the transmitter periodically sends authentication information using its private key. Therefore, the transmitter's private key should never be compromised.

In an alternative embodiment shown in fig. 46, the keys may be distributed directly from the WAPS server to the receiver over the communication link, or may be routed through a third party application or service provider. The key may have a certain validity period. The keys may be made available per application or per device based on a contract with the customer. Each time an application on the receiver or on the network makes a location request, the validity of the key is checked before retrieving the location or parameters for calculating the location from the WAPS engine. The key and information exchange to the WAPS server may be done using a proprietary protocol or through a standard protocol such as OMA SUPL.

The security architecture of the system may be implemented as a combination of the architectures shown in fig. 44 and 46.

The parameter sensors may be integrated into the receiver of the WAPS system to time tag and/or place tag the measurements from the sensors. The parameter sensors may include, but are not limited to, temperature sensors, humidity sensors, weight sensors, and scanner-type sensors, to name a few. For example, an X-ray detector may be used to determine whether a tracked receiver or a device including a tracked receiver has passed through an X-ray machine. The detector can tag the time of the X-ray event and the location of the X-ray machine. Additionally, other parameter sensors may be integrated into the WAPS system to time tag and location tag both the measurements from the sensors.

The user may be charged for the system on a per use, per application to the device, hourly, daily, weekly, monthly, and yearly basis for an individual or asset. The location and height of the receiver unit may be transmitted using a communication protocol to any application on the terminal or to a network server. Alternatively, raw range measurements may be sent to the network via a communication protocol. The communication protocol may be a standard serial or other digital interface to an application on the terminal or to the server through a standard or proprietary wireless protocol. A possible method of coupling or connecting to the server via a standard protocol includes using an SMS message to another phone connected to the server or alternatively to a web server via a wireless data service. The transmitted information includes one or more of latitude/longitude, altitude (if available), and a timestamp. An application on the server or terminal unit may initiate position location. The user's location may be transmitted directly from the server or through an application on the server.

The location of the device may be determined using a WAPS independent system independent of the GPS receiver. The WAPS system itself, or a WAPS system integrating the WAPS and GPS and/or other positioning systems, may be implemented to coexist on a media card with a media memory card (such as an SD card). The WAPS system itself, or a WAPS system integrating the WAPS and GPS systems and/or other positioning systems, may be implemented to co-exist with a Subscriber Identity Module (SIM) card on the cellular telephone so that the SIM card can be tracked.

Precision positioning by carrier phase

One way to extend the performance of WAPS systems to further improve accuracy (up to <1m) is to implement a carrier-phase positioning system as described below. The beacon is set as in a normal WAPS transmitter. For this approach, it is desirable (but not required) to not use TDMA time slots to facilitate continuous phase tracking. The near-far problem can be overcome by interference cancellation in the receiver and increased dynamic range when TDMA is not used. A WAPS receiver supporting this method is able to measure the code and carrier phase in a continuous manner for all satellites in view and time stamp them. In addition, there are reference receivers at known survey sites, which can also make similar measurements of code and carrier phase in a continuous manner. The measurements from the WAPS receiver and the reference receiver may be combined and the position calculated on the device or on the server. This system is configured identically to the differential WAPS system.

The carrier phase measurement is more accurate than the code phase measurement, but contains an unknown integer number of carrier phase periods known as integer ambiguity. However, there are ways to find integer ambiguities, called ambiguity solutions. Consider here a method that uses an extension of the local minimum search algorithm, iteratively solves for user receiver position, and uses measurements over multiple epochs to improve accuracy.

First, the carrier phase measurements at the user receiver for a single epoch are considered as follows.

Where φ, λ, f and N are carrier phase, wavelength, frequency and integer period, respectively, dt is clock offset, r is range, ε is measurement error, subscript u denotes user receiver, k denotes transmitter number.

According to user and receiver position p_uAnd p^(k)The range is given as

To eliminate errors in the knowledge of the transmitter clock offset, another receiver at a known location (called the reference receiver) is considered using the corresponding carrier phase equation

Wherein the subscript r represents the reference receiver, obtained by subtracting (2) from (1)

It writes

Wherein, (.)_ur=(·)_u-(·)_r。

Due to no concern about dt_ur, which can therefore be eliminated by differentiating (5) against the difference of index (k), to obtain the so-called double-difference observation equation

Wherein,

then, equation (6) is passedUnknown user position p_uThe equation in (1) is as follows

Wherein,

(8) γ^(kl)=||p_r-p^(k)||-||p_r-p^(l)||

in general, the transmitter l used in the bidifferencing is one of the transmitters, and marking it as 1 for convenience produces an equation in the form of a matrix as follows

Or

(lO) φ=λ^-1·f(p_u)+N+ε

Equation (10) is the unknown user position p_uIs used as a non-linear equation. The local minimum search algorithm works on linear equations, so (10) is linearized and solved iteratively as follows. Set at iteration m, for p_uIs approximately ofWherein

And is

Wherein,

wherein l^(k)Is a line of sight line row vector

Then, the equation (10) is written,

(13) y = G · x · + N + ε, wherein, and x = Δ p_u

Equation (13) at x = Δ p_uIs linear in time and is directed to Δ p using the local minimum search algorithm given below_uAnd (6) solving. Using the thus obtained Δ p_uUsing equation (11) to obtain p at iteration m_uThen using p thus obtained_uAs at the next iteration (m +1). The iteration is continued until Δ p_uBecomes small enough to decide on convergence. At the start of an iteration, it can be obtained from a code phase based solution。

Now consider solving equation (13). Let Q_ddIs the covariance matrix of the double difference carrier phase error vector. It was obtained as follows. Single difference observationThe variance of the error of (2) is Q_u+Q_rWherein Q is_uAnd Q_rRespectively, assuming a carrier phase error variance independent of transmitter k.Is 2 (Q)_u+Q_r) And is andandthe cross variance between j ≠ k is Q_u+Q_rWhich is a common itemThe variance of (c). Therefore, the temperature of the molten metal is controlled,

(13) the weighted least squares solution of (c) is:

wherein G is^LIs the left-hand inverse of G,

the vector of the residual is then

Which is a function of N, a local minimum search attempts to minimize the weighted norm square of the residual for N, as follows

(17) min c(N)=(y-N)^TW (y-N), wherein,and S = I-G^L

To solve (17), consider the constraint that N is an integer, and solve the following equation

(18) W·N≈W·y。

Then, W (y-N) ≈ 0, and

(y-N)^T·W^T·W·(y-N)=(y-N)^Tw- (y-N) = c (N) ≈ O because W is important (W)^T= W and W · W = W). Therefore, the search for N is limited to N satisfying (18).

Once N is found, the estimated value obtained from equation (15). Matrices G and G having dimensions (n-1) × 3 and 3 × (n-1), respectively^LEach having a rank of 3, the matrices S and W of (n-1) × (n-1) will be 3 shorter than the full rank of (n-1) because (n-1) > 3.

QR decomposition (LU decomposition may also be used) is used for W on equation (18),

(19) R·N=Q^T·W·y

wherein Q is an orthogonal matrix (Q)^-1=Q^T) And R is an upper triangular matrix, thereby

Then, the user can use the device to perform the operation,

thus, by searching for N in a 3-dimensional box (box) having integer values₂Obtaining N from (21)₁And picking up the N that makes c (N) in (17) small to obtainThe solution of (1). Searching for N₂With N from the previous iteration₂Is the center. At the zeroth iteration N₂When is serving asThe second half of N obtained from the fractional part of (a);is a solution based on the code phase. The size of the 3-dimensional search bin depends on the uncertainty of the solution based on the code phase. The bin may be divided into smaller sub-bins and the center of each smaller sub-bin may be tried as the initial。

The above method uses single epoch (instantaneous) measurements to determine position. The following description illustrates an extension to the single epoch method. Multiple epoch measurements are taken that are close enough in time that user receiver movement is negligible. Furthermore, the integer ambiguity of the initial epoch remains the same over subsequent epochs, so that no new unknown integer ambiguities are introduced at subsequent epochs. Because the transmitter location is fixed, the multi-epoch measurement does not give an independent equation (unlike in the case of GNSS, where the motion of the satellite transmitter changes the line of sight, thus giving an independent equation). Thus, multi-epoch measurements do not help when solving for integer ambiguities as floating ambiguities (unlike in the case of GNSS when the number of independent equations becomes greater than the unknown ambiguities plus the number of three unknown coordinates). However, multi-epoch measurements allow for greater carrier phase measurement errors and still allow for successful ambiguity resolution. In the case of multiple epochs, equation (13) becomes

Following the expansion of the equation as above for the single epoch case, the problem reverts to that of finding N, such that the following holds

Wherein,

in order to solve the N pair (23), the use thereof is consideredIs performed (LU decomposition may also be used), and following equations (19) to (21) as above, the following equation is solved

Wherein,

once again, once N is solved, x = Δ p is obtained from equation (15)_uAn estimate of (d). If the x = Δ p_uIs small, the iteration in equation (11) is stopped to obtain the user position p_u. In general, if the magnitude of each component of x is less than le-6, convergence is declared and the iteration stops.

The next step is to verify the converged user position p_uWhether it is the correct location. This is based on the equation as mod (φ - λ)^-1·f(p_u) -N, λ) is performed from the residual obtained from (10). If the maximum value of the absolute value of the residual error of each epoch (epoch) is less thanThe converged solution is accepted as the solution, otherwise the search is continued by selecting a new sub-box. In general, the scaling factor κ in the validation test may be chosen to be 5. Once the solution is validated, the differential WAPS system described above can achieve an accuracy of close to or better than 1 m.

The differential WAPS carrier-phase system may be superimposed on the conventional WAPS system by adding a reference receiver, or may be independent. The differential WAPS carrier-phase system can be used to deliver high accuracy position fixes in specific localized target areas (e.g., shopping malls, warehouses, etc.).

In a W-CDMA system, two receive chains are used to improve receive diversity. When WAPS coexists with W-CDMA, one of the receive chains may be temporarily used for receiving and processing the WAPS signal. In some cases of the W-CDMA and CDMA architectures, the entire receive chain may be reused to receive the WAPS signal by tuning the receiver to the WAPS band and processing the WAPS signal while temporarily suspending the processing of the W-CDMA/CDMA signal. In some other embodiments where the GSM receive chain is multiplexed with the W-CDMA receive chain, the receiver may be further time-shared for WAPS reception.

Once it is determined that position determination is to be made in a WAPS or any other TDMA system using those signals from those signal towers, the receiver of most embodiments is turned off during time slots in which no signals are detected and/or position determination is to be made without using signals from the signal towers radiating in those time slots, in order to save power. In the event that a position movement or change is detected or a signal condition changes, then the receiver of an embodiment is turned on in all time slots to determine which time slots can be used for the next set of position calculations.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a reference sensor array comprising at least one reference sensor cell located at a known location. The system comprises: a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver. The system comprises: a positioning application running on a processor and coupled to the remote receiver. The positioning application calculates the position of the remote receiver using the atmospheric data, reference data from a set of reference sensor units of the reference sensor array, and information derived from at least one of the positioning signals and satellite signals, the satellite signals being signals of a satellite based positioning system. The location includes an altitude.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a reference sensor array comprising at least one reference sensor cell located at a known location; a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver; and a positioning application running on a processor and coupled to the remote receiver, wherein the positioning application calculates a position of the remote receiver using the atmospheric data, reference data from a set of reference sensor units of the reference sensor array, and information derived from at least one of the positioning signals and satellite signals, the satellite signals being signals of a satellite-based positioning system, wherein the position includes an altitude.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a reference sensor array comprising at least one reference sensor cell located at a known location. The system comprises: a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver. The system comprises: a positioning application running on a processor and coupled to the remote receiver. The positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from a set of reference sensor units of the reference sensor array. The positioning application calculates the position of the remote receiver using the reference pressure estimate and information derived from at least one of the positioning signals and satellite signals, the satellite signals being signals of a satellite-based positioning system. The location includes an altitude.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a reference sensor array comprising at least one reference sensor cell located at a known location; a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver; and a positioning application running on a processor and coupled to the remote receiver, wherein the positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from a set of reference sensor units of the reference sensor array, wherein the positioning application calculates the location of the remote receiver using the reference pressure estimate and information derived from at least one of the positioning signals and satellite signals, the satellite signals being signals of a satellite-based positioning system, wherein the location comprises an altitude.

The location application of an embodiment resides on the remote receiver and the remote receiver calculates the location.

The remote receiver of an embodiment operates in a reduced power state when the locating signal is at least one of undetected and unavailable.

The remote receiver of an embodiment determines a position using a set of positioning signals from a set of the plurality of transmitters, wherein the remote receiver operates in a reduced power state when the set of positioning signals is at least one of undetected and unavailable.

The remote receiver of an embodiment transitions from the reduced power state to a full power state in response to detecting at least one of a motion of the remote receiver, a change in position of the remote receiver, and a change in signal conditions of the positioning signal.

The system of an embodiment comprises a server coupled to the remote receiver, wherein the positioning application resides on the server and the server calculates the position.

The system of an embodiment comprises a server coupled to the remote receiver, wherein the positioning application is distributed between the remote receiver and the server.

A first mode of operation of the remote receiver of an embodiment includes a terminal-based positioning in which the remote receiver calculates the location.

A second mode of operation of the remote receiver of an embodiment includes the server computing a network-based location of the location.

The known location of an embodiment is the location of a group of transmitters of the plurality of transmitters.

The positioning application of an embodiment comprises a pressure surface gradient model that generates an equivalent reference elevation pressure at the location of the remote receiver using the reference data from the set of reference sensor units.

The positioning application of an embodiment uses the equivalent reference altitude pressure as a reference value for generating the altitude.

The positioning application of an embodiment generates an equivalent reference altitude pressure for each reference sensor unit of the set of reference sensor units using the reference data from each reference sensor unit.

The reference data of an embodiment comprises pressure, temperature and location data for each reference sensor unit of the set of reference sensor units, wherein the location data comprises altitude.

The positioning application of an embodiment generates the equivalent reference altitude pressure at the location of the remote receiver using the equivalent reference altitude pressure for each reference sensor unit in the set of reference sensor units and the latitude and longitude of the remote receiver.

The positioning application of an embodiment generates the altitude of the remote receiver using the atmospheric data at the location of the remote receiver and the equivalent reference altitude pressure.

At least one emitter of the plurality of emitters is assigned to at least one reference sensor unit of an embodiment.

The at least one reference sensor unit of an embodiment comprises a plurality of reference sensor units, wherein a first group of the plurality of transmitters is assigned to a first group of the plurality of reference sensor units and a second group of the plurality of reference sensor units is at a location different from locations of the plurality of transmitters.

At least one reference sensor unit of an embodiment is at a location different from the locations of the plurality of transmitters.

An atmospheric sensor of an embodiment collects pressure and temperature at the location of the remote receiver.

The atmospheric sensor of an embodiment determines pressure data with a resolution approximately in the range of less than 36 pascals.

The remote receiver of an embodiment detects a rate of change of the pressure data.

The positioning application of an embodiment uses the rate of change to determine the vertical velocity of the remote receiver.

The temperature data of an embodiment includes an outside air temperature at the location of the remote receiver, and the atmospheric sensor determines the temperature data at a resolution at least one of approximately equal to and less than 3 degrees celsius.

Each reference sensor unit of an embodiment includes at least one atmospheric reference sensor that collects reference pressure and reference temperature data at a known location of the atmospheric reference unit.

The at least one atmospheric reference sensor of an embodiment determines the reference pressure data with a resolution approximately in the range of 2-36 pascals.

The reference temperature data of an embodiment comprises an outside air temperature at the known location, and the atmospheric reference sensor determines the temperature data at a resolution at least one of approximately equal to and less than 3 degrees celsius.

An atmospheric reference sensor of an embodiment is calibrated for a limited temperature range, wherein the limited temperature range is determined based on a temperature experienced by the atmospheric reference sensor.

Each atmospheric reference sensor of an embodiment continuously collects reference pressure and reference temperature data at the known location.

The atmospheric reference sensor of an embodiment is positioned to collect a reference pressure and a reference temperature in relatively stationary air.

The atmospheric reference sensor of an embodiment filters the reference pressure and reference temperature data.

The atmospheric reference sensor of an embodiment filters the reference pressure and reference temperature data using an adaptive time scale.

Each reference sensor unit of an embodiment comprises a wind detector that detects wind data, wherein the wind data comprises a direction and a magnitude of a local wind.

The positioning application of an embodiment uses the wind data to at least one of correct and filter the variable in the atmospheric sensor.

The at least one reference sensor unit of an embodiment comprises a plurality of atmospheric reference sensors.

The system of an embodiment includes a communication link coupled between the reference sensor array and the remote receiver.

The reference sensor array of an embodiment broadcasts atmospheric reference data.

The reference sensor array of an embodiment broadcasts raw data of the atmospheric reference data.

The reference sensor array of an embodiment broadcasts differential data of the reference data.

Differential data for an embodiment is derived relative to at least one constant value.

The differential data of an embodiment includes differential pressure data derived as an offset value of standard atmospheric pressure.

The remote receiver of an embodiment receives the reference data via the broadcast.

The reference sensor array of an embodiment broadcasts the reference data multiple times per second.

The reference sensor array of an embodiment broadcasts the reference data a plurality of times per measurement.

The remote receiver of an embodiment determines a set of atmospheric reference sensors to interrogate to extract (pull) the reference data from the set of atmospheric reference sensors via the communication link.

The positioning application of an embodiment processes the reference data and determines an equivalent reference altitude pressure for each reference sensor unit in the set of reference sensor units.

The reference data of an embodiment includes a location of each atmospheric reference cell.

The location of an embodiment includes a latitude and a longitude.

The location of an embodiment includes an elevation.

The reference data of an embodiment includes measured outside air temperature from each atmospheric reference cell.

The baseline data of an embodiment includes a confidence level.

Each reference sensor unit of an embodiment processes the reference data of that reference sensor unit and determines an equivalent reference altitude pressure of the reference sensor unit.

The reference data of an embodiment includes the location of each atmospheric reference sensor.

The location of an embodiment includes a latitude and a longitude.

The location of an embodiment includes an elevation.

The reference data of an embodiment comprises said equivalent reference altitude pressure.

The baseline data of an embodiment includes a confidence level.

The altitude of an embodiment includes an estimated altitude for each floor in the at least one structure.

The system of an embodiment comprises a database coupled to a plurality of remote receivers including the remote receiver, wherein the database comprises the estimated altitudes received from the plurality of remote receivers.

The system of an embodiment comprises a learning application coupled to the server, wherein the learning application processes the estimated altitudes of the plurality of remote receivers and revises the database using the estimated altitudes.

The at least one reference sensor unit of an embodiment comprises at least one local reference sensor unit that is local to at least one of the site and the structure.

The reference data of an embodiment comprises data of the at least one local reference sensor unit.

The system of an embodiment comprises: automatically calibrating the atmospheric sensor of the remote receiver using the aggregated reference data over a specified time period.

The system of an embodiment comprises: the aggregated reference data is generated by discerning when the remote receiver is at a known location, accumulating deviations of the atmospheric data corresponding to the known location, and generating a corrected calibration from the accumulated deviations.

The system of an embodiment comprises: automatically calibrating the atmospheric sensor of the remote receiver when an altitude and an atmospheric pressure of the location of the remote receiver are known.

The position of the remote receiver of an embodiment is determined using the satellite signals.

The system of an embodiment comprises: the altitude is determined using a reference altitude.

The reference altitude of an embodiment minimizes an altitude difference between altitudes calculated using at least one of the atmospheric data and the reference data.

The reference altitude of an embodiment comprises an average altitude of the atmospheric reference unit.

The reference altitude of an embodiment comprises an average altitude of an area in which the remote receiver is located.

The altitude of an embodiment comprises an estimated altitude derived using local constraint data.

The local limit data of an embodiment comprises terrain data of terrain in the vicinity of the location of the remote receiver.

The local limit data of an embodiment comprises an altitude of at least one structure near the location of the remote receiver.

The local limit data of an embodiment comprises an altitude of at least one other remote receiver in proximity to the location of the remote receiver.

The positioning application of an embodiment determines the altitude using the atmospheric data, the reference data, and the local limit data.

The system of an embodiment comprises a database coupled to the positioning application, wherein the database comprises historical data measured during a period of time, wherein the historical data comprises the reference data of the reference sensor array and atmospheric data of a plurality of remote receivers.

The location application of an embodiment uses the historical data to determine the altitude.

The system of an embodiment comprises: optimizing the at least one reference sensor cell of the reference sensor array using the historical data.

The system of an embodiment comprises: the altitude is determined by relaxing the assumption of a constant equivalent reference altitude pressure between the reference location of the reference sensor unit and the current position of the remote receiver.

The system of an embodiment comprises: converting the first equivalent reference altitude pressure at the reference location to a second equivalent reference altitude pressure at a standard temperature. The system of an embodiment comprises: a local temperature at the current location is determined and the second equivalent reference altitude pressure is converted to a third equivalent reference altitude pressure using the local temperature. The system of an embodiment comprises: determining an altitude at the current location using the third equivalent reference altitude pressure.

The system of an embodiment comprises: using the reference data at each reference sensor unit in the set of reference sensor units, a change in equivalent reference altitude pressure relative to the horizontal location is determined. The system of an embodiment comprises: determining a best estimate of a reference altitude pressure at the current location by combining the equivalent reference altitude pressures of the set of reference sensor units.

The best estimate of the equivalent reference altitude pressure of an embodiment comprises using a weighted averaging technique, wherein the weight is a function of the horizontal distance between the location of the reference sensor unit and said current position.

Embodiments determine the best estimate of the equivalent reference altitude pressure include: using a least squares fit to create a second order surface that best fits the calculated sea level pressure at each reference sensor cell of the set of reference sensor cells; and interpolating the best estimate of the equivalent reference altitude pressure at the current location using an nth order surface.

The system of an embodiment comprises: converting the first equivalent reference altitude pressure at each reference sensor unit in the set of reference sensor units to a second equivalent reference altitude pressure at a standard temperature. The system of an embodiment comprises: determining a best estimate of the equivalent reference altitude pressure at the current location by combining the second equivalent reference altitude pressure from each reference cell.

Embodiments determine the best estimate of the equivalent reference altitude pressure comprises using a weighted averaging technique in which the weight is a function of the horizontal distance between the location of the reference sensor unit and the current position.

Embodiments determine the best estimate of the equivalent reference altitude pressure include: using a least squares fit to create a second order surface that best fits the calculated equivalent reference altitude pressure at each reference sensor unit in the set of reference sensor units; and interpolating the best estimate of sea level pressure at the current location using an nth order surface.

The remote receiver of an embodiment includes a high speed clock.

The remote receiver of an embodiment receives pulse edges from a common time reference, wherein the remote receiver uses the high speed clock to determine a time difference between an occurrence of the pulse edges and a rising edge of a sample clock.

The remote receiver of an embodiment applies a correction to the estimated range based on the time difference, wherein the correction improves the accuracy of the estimated range.

The remote receiver of an embodiment comprises a correlator for correlating a received signal with a pseudorandom code, wherein the correlator comprises a first shift register comprising a plurality of sets of second shift registers in series, the second shift registers having parallel random access read capability.

Each of the plurality of sets of second shift registers of an embodiment includes a plurality of shift register group cells connected in series.

Each shift register group cell of an embodiment includes an n-bit shift register group cell.

Each shift register group cell of the embodiment includes a 16-bit shift register group cell.

Each set of second shift registers of an embodiment forms a 32-bit shift register.

The serially connected sets of second shift registers of an embodiment comprise sets of n-bit shift registers.

The serially connected sets of second shift registers of an embodiment include 32 sets of second shift registers, wherein the first shift register is a 1024-bit shift register.

The shifting operation of the first shift register of an embodiment occurs at a clock rate of a clock coupled to the correlator.

The read out operation of the first shift register of an embodiment occurs at a speed of at least twice the clock rate.

The read out operation of the first shift register of an embodiment occurs at 32 times the clock rate.

The system of an embodiment includes a plurality of adders in series coupled to outputs of the series of sets of second shift registers.

The plurality of adders in the series of embodiments include an adder tree, wherein the adder tree includes adder cells that are wider in width.

The plurality of adders in the series of embodiments include adders coupled to each of the plurality of sets of n-bit shift registers.

The plurality of adders in series of an embodiment includes a first adder coupled to outputs of the first plurality of sets of second shift registers, a second adder coupled to outputs of the second plurality of sets of second shift registers, a third adder coupled to outputs of the third plurality of sets of second shift registers, and a fourth adder coupled to outputs of the fourth plurality of sets of second shift registers.

The system of an embodiment includes an end adder coupled to the outputs of the plurality of adders in the series.

The system of an embodiment comprises: aligning outputs of the series of the plurality of adders in the series of the plurality of groups of the end adders.

In the end adders, the output of the first adder of the embodiment is aligned in a first group, the output of the second adder is aligned in a second group, the output of the third adder is aligned in a third group, and the output of the fourth adder is aligned in a fourth group.

The end adders of an embodiment form a sum by adding the contents of the plurality of adders in series.

The remote receiver of an embodiment temporarily uses a local receive chain of a plurality of local receive chains of the remote receiver to acquire the at least one of the positioning signal and the satellite signal.

The plurality of local receive chains of an embodiment include a diversity receive chain that improves receive diversity.

The remote receiver of an embodiment comprises a wide bandwidth receiver.

The remote receiver of an embodiment comprises a wide bandwidth cellular band receiver.

The remote receiver of an embodiment uses the diversity receive chain at least one of temporarily and permanently to acquire the positioning signal.

104. The positioning system of claim 2, comprising a communication system coupled to the remote receiver and at least one of the plurality of transmitters, wherein the communication system is a cellular communication system.

The plurality of transmitters of an embodiment are synchronized to, wherein each transmitter of the plurality of transmitters transmits a signal comprising a pseudo random number sequence and assistance data.

Assistance data of an embodiment includes at least one of system time at a rising edge of a mid-pulse waveform, system time at a falling edge of a pulse waveform, geocode data for the plurality of transmitters, geocode data for a neighboring transmitter neighboring the plurality of transmitters, an index of a sequence used by at least one transmitter proximate the plurality of transmitters, a clock timing correction value for at least one transmitter, a local atmospheric correction value, a relationship of WAPS timing to GNSS timing, at least one of an indication of a local environment that assists the remote receiver in pseudorange solving and an offset from a base index of a set of pseudorandom sequences, a list of pseudorandom number sequences from a set of transmitters, and a list of transmitters that use a particular pseudorandom number sequence.

The positioning application of an embodiment calculates the position of the remote receiver by formulating a set of equations as a non-linear objective function and generating a best estimate of the position as a set of position parameters that minimize the objective function.

The positioning application of an embodiment calculates the position of the remote receiver by formulating a set of linearized equations and solving the set of linearized equations using least squares.

The positioning application of an embodiment calculates the location of the remote receiver using an approximate location of a group of transmitters of the plurality of transmitters and Received Signal Strength (RSS) data of the group of transmitters.

The location application of an embodiment calculates the location of the remote receiver by storing a sample segment of the location signal in the remote receiver, then processing the sample segment to search, acquire, and calculate ranges to the plurality of transmitters.

The positioning application of an embodiment uses received signal strength data of the remote receiver to calculate the location of the remote receiver.

The positioning application of an embodiment calculates the position of the remote receiver using at least one of carrier phase data and code phase data of the positioning signal.

The positioning application of an embodiment uses differential positioning with respect to at least one reference receiver to calculate the position of the remote receiver.

The positioning application of an embodiment calculates the position of the remote receiver using at least one of range measurements and representations of range measurements from signals of opportunity received from a positioning system, a Global Navigation Satellite System (GNSS), a Global Positioning System (GPS), a differential positioning system, radio signals, television signals, a wireless network system, a WiFi system, a cellular system, and a bluetooth system.

The positioning application of an embodiment calculates a final position of the remote receiver using range measurements from at least one additional signal source combined with range measurements determined using the positioning signals, wherein the final position includes at least one of latitude, longitude, and altitude.

The positioning application of an embodiment uses range measurements from at least one additional signal source combined with range measurements determined using the positioning signals, and a position quality metric from the at least one additional signal source, to compute an optimized location solution for the remote receiver.

The positioning application of an embodiment calculates the position of the remote receiver using a hybrid positioning that includes measurements from the positioning signals and measurements from at least one additional source.

The positioning system information of an embodiment includes timing synchronization and corresponding correction information.

Embodiments described herein include a reference system comprising: and a reference sensor array including at least one set of reference sensor cells. Each group includes at least one reference sensor unit located at a known location. The system comprises: a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver. The system comprises: a positioning application running on a processor and coupled to the remote receiver, wherein the positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from the at least one set of reference sensor units of the reference sensor array. The positioning application calculates an altitude of the remote receiver using the reference pressure estimate.

Embodiments described herein include a reference system comprising: a reference sensor array comprising at least one set of reference sensor cells, wherein each set comprises at least one reference sensor cell located at a known location; a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver; and a positioning application running on a processor and coupled to the remote receiver, wherein the positioning application generates a reference pressure estimate at the location of the remote receiver using the atmospheric data and reference data from the at least one set of reference sensor units of the reference sensor array, wherein the positioning application calculates an altitude of the remote receiver using the reference pressure estimate.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a remote receiver acquiring at least one of the positioning signal and a satellite signal. The satellite signals are signals of a satellite based positioning system. The first mode of operation of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from at least one of the positioning signals and the satellite signals. The remote receiver comprises a correlator which correlates the received signal with a pseudo-random code; and a server coupled to the remote receiver. The second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals. The remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a remote receiver that acquires at least one of the positioning signal and a satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, wherein a first mode of operation of the remote receiver comprises a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from the at least one of the positioning signal and the satellite signal, wherein the remote receiver comprises a correlator that correlates a received signal with a pseudorandom code; and a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals, wherein the remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

The correlator of an embodiment includes a first shift register comprising a plurality of sets of second shift registers in series, the second shift registers having parallel random access reading capability.

Each of the plurality of sets of second shift registers of an embodiment includes a plurality of shift register group cells connected in series.

Each shift register group cell of an embodiment includes an n-bit shift register group cell.

Each shift register group cell of the embodiment includes a 16-bit shift register group cell.

Each set of second shift registers of an embodiment forms a 32-bit shift register.

The serially connected sets of second shift registers of an embodiment comprise sets of n-bit shift registers.

The serially connected sets of second shift registers of an embodiment include 32 sets of second shift registers, wherein the first shift register is a 1024-bit shift register.

The shift operation of the first shift register of an embodiment occurs at a clock rate coupled to the associated clock.

The read out operation of the first shift register of an embodiment occurs at a speed of at least twice the clock rate.

The read out operation of the first shift register of an embodiment occurs at 32 times the clock rate.

The system of an embodiment includes a plurality of adders in series coupled to outputs of the series of sets of second shift registers.

The plurality of adders in the series of embodiments include an adder tree, wherein the adder tree includes adder cells that are wider in width.

The plurality of adders in the series of embodiments include adders coupled to each of the plurality of sets of n-bit shift registers.

The plurality of adders in series of an embodiment includes a first adder coupled to outputs of the first plurality of sets of second shift registers, a second adder coupled to outputs of the second plurality of sets of second shift registers, a third adder coupled to outputs of the third plurality of sets of second shift registers, and a fourth adder coupled to outputs of the fourth plurality of sets of second shift registers.

The system of an embodiment includes an end adder coupled to the outputs of the plurality of adders in the series.

The system of an embodiment comprises: aligning outputs of the series of the plurality of adders in the series of the plurality of groups of the end adders.

In the end adders, the output of the first adder of the embodiment is aligned in a first group, the output of the second adder is aligned in a second group, the output of the third adder is aligned in a third group, and the output of the fourth adder is aligned in a fourth group.

The end adders of an embodiment form a sum by adding the contents of the plurality of adders in series.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a remote receiver acquiring at least one of the positioning signal and a satellite signal. The satellite signals are signals of a satellite based positioning system. The first mode of operation of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from at least one of the positioning signals and the satellite signals. When the locating signal is not detected, the remote receiver operates in a reduced power state. The system comprises: a server coupled to the remote receiver. The second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals. The remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a remote receiver that acquires at least one of the positioning signal and a satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, wherein a first operating mode of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from the at least one of the positioning signal and the satellite signal, wherein the remote receiver operates in a reduced power state when the positioning signal is not detected; and a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals, wherein the remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

The location application of an embodiment resides on the remote receiver and the remote receiver calculates the location.

The remote receiver of an embodiment operates in a reduced power state when the locating signal is at least one of undetected and unavailable.

The remote receiver of an embodiment determines a position using a set of positioning signals from a set of the plurality of transmitters, wherein the remote receiver operates in a reduced power state when the set of positioning signals is at least one of undetected and unavailable.

The remote receiver of an embodiment transitions from the reduced power state to a full power state in response to detecting at least one of a motion of the remote receiver, a change in position of the remote receiver, and a change in signal conditions of the positioning signal.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a remote receiver acquiring at least one of the positioning signal and a satellite signal. The satellite signals are signals of a satellite based positioning system. The first mode of operation of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from at least one of the positioning signals and the satellite signals. The remote receiver includes a high speed clock. The system comprises: a server coupled to the remote receiver. The second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates the position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals. The remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a remote receiver that acquires at least one of the positioning signal and a satellite signal, wherein the satellite signal is a signal of a satellite-based positioning system, wherein a first mode of operation of the remote receiver comprises a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from the at least one of the positioning signal and the satellite signal, wherein the remote receiver comprises a high-speed clock; and a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals, wherein the remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

The remote receiver of an embodiment receives pulse edges from a common time reference, wherein the remote receiver uses the high speed clock to determine a time difference between an occurrence of the pulse edges and a rising edge of a sample clock.

The remote receiver of an embodiment applies a correction to the estimated range based on the time difference, wherein the correction improves the accuracy of the estimated range.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast positioning signals, the positioning signals comprising at least ranging signals and positioning system information. The ranging signal includes information for measuring a distance to a transmitter broadcasting the ranging signal. The system comprises: a remote receiver acquiring at least one of the positioning signal and a satellite signal. The remote receiver temporarily acquires the at least one of the positioning signal and the satellite signal using a local receive chain of a plurality of local receive chains of the remote receiver. The satellite signals are signals of a satellite based positioning system. The first mode of operation of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from at least one of the positioning signals and the satellite signals. The system comprises: a server coupled to the remote receiver, wherein a second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals. The remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

Embodiments described herein include a positioning system comprising: a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein the ranging signal comprises information for measuring a distance to the transmitter broadcasting the ranging signal; a remote receiver that acquires at least one of the positioning signal and a satellite signal, wherein the remote receiver temporarily acquires the at least one of the positioning signal and the satellite signal using a local receive chain of a plurality of local receive chains of the remote receiver, wherein the satellite signal is a signal of a satellite-based positioning system, wherein a first mode of operation of the remote receiver includes a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from the at least one of the positioning signal and the satellite signal; and a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from information derived from at least one of the positioning signals and the satellite signals, wherein the remote receiver receives and communicates to the server information derived from at least one of the positioning signals and the satellite signals.

The remote receiver of an embodiment temporarily uses a local receive chain of a plurality of local receive chains of the remote receiver to acquire the at least one of the positioning signal and the satellite signal.

The plurality of local receive chains of an embodiment include diverse receive chains that improve receive diversity.

The remote receiver of an embodiment comprises a wide bandwidth receiver.

The remote receiver of an embodiment comprises a wide bandwidth cellular band receiver.

The remote receiver of an embodiment uses the diverse receive chains at least one of temporarily and permanently to acquire the positioning signals.

The system described herein for use in position/timing accuracy may be used in one or more of the following applications, both local and wide area, but is not limited to the following applications: asset tracking; tracking people; tracking the pet; fire safety; moving the advertisement; special location determination for public safety applications (e.g., a group of "mobile" transmitters may be moved to a location (e.g., a fire location), and these transmitters will form a local network to provide location information to a group of receivers in its vicinity); military applications (e.g., transmitters may be deployed in a particular manner, either on land or in the air, to obtain precise indoor locations); a strongly adaptive bandwidth for applications that can provide bandwidth that meets accuracy requirements; container tracking and vehicles moving containers around in an indoor environment; a geographic marker; a geographic definition; an E911 application; palette tracking for medical applications and other applications requiring palette tracking; a femto cell; a timing reference for a femto cell, timing receiver; providing a location of the authenticated security application based on both the indoor and outdoor locations; home applications (e.g., pet/asset tracking using WAPS, and walking navigation of assets/pets using mobile phones). The WAPS system itself, or a WAPS system integrated with other location technologies, may be further integrated into an existing local and/or wide area asset tracking and/or positioning system.

Embodiments described herein include a positioning system comprising: a transmitter network comprising a plurality of transmitters that broadcast positioning signals; a remote receiver that acquires and tracks at least one of the positioning signals and satellite signals, wherein the satellite signals are signals of a satellite-based positioning system, wherein a first mode of operation of the remote receiver comprises a terminal-based positioning in which the remote receiver calculates a position of the remote receiver from the at least one of the positioning signals and the satellite signals; and a server coupled to the remote receiver, wherein the second mode of operation of the remote receiver comprises a network-based positioning in which the server calculates a position of the remote receiver from at least one of the positioning signals and the satellite signals, wherein the remote receiver receives and communicates to the server at least one of the positioning signals and the satellite signals.

Embodiments described herein include a method of determining a location, comprising: receiving at least one of a positioning signal and a satellite signal at a remote receiver, wherein the positioning signal is received from a transmitter network comprising a plurality of transmitters, wherein the satellite signal is received from a satellite-based positioning system; and determining a position of the remote receiver using one of a terminal-based positioning and a network-based positioning, wherein the terminal-based positioning includes calculating the position of the remote receiver at the remote receiver using at least one of the positioning signals and the satellite signals, wherein the network-based positioning includes calculating the position of the remote receiver at the remote server using at least one of the positioning signals and the satellite signals.

The components described herein may be located together or in separate locations. A communication path couples the components and includes any medium for transferring or transferring files between the components. The communication path includes a wireless connection, a wired connection, and a hybrid wireless/wired connection. The communication path also includes a coupling or connection to a network including a Local Area Network (LAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a private network, a local or back end network, and the Internet. In addition, the communication path includes removable fixed media like floppy disks, hard drives, and CD-ROM disks, as well as flash RAM, Universal Serial Bus (USB) connections, RS-232 connections, telephone lines, buses, and e-mail messages.

Aspects of the systems and methods described herein may be implemented as functionality programmed into any of a variety of circuits including Programmable Logic Devices (PLDs) including Field Programmable Gate Arrays (FPGAs), Programmable Array Logic (PAL) devices, electrically programmable logic and memory devices and standard cell based devices, and Application Specific Integrated Circuits (ASICs). Some other possibilities for implementing aspects of the systems and methods include: a microcontroller having a memory, such as an electrically erasable programmable read-only memory (EEPROM), an embedded microprocessor, firmware, software, etc. Furthermore, aspects of the systems and methods may be implemented in microprocessors having software-based circuit emulation, discrete logic (sequential and combinatorial), custom devices, fuzzy (neural) logic, quantum devices, and hybrids of any of the above device types. Of course, the underlying device technologies may be provided in a variety of component types, such as Metal Oxide Semiconductor Field Effect Transistor (MOSFET) technologies like Complementary Metal Oxide Semiconductor (CMOS), bipolar technologies like Emitter Coupled Logic (ECL), polymer technologies (e.g., silicon conjugated polymer and metal conjugated polymer-metal structures), mixed analog and digital, and so forth.

Note that any of the systems, methods, and/or other components disclosed herein can be described using computer-aided setup tools and expressed (or represented) in terms of their behavioral, register transfer, logic component, transistor, layout geometries, and/or other characteristics as data and/or instructions embodied in various computer-readable media. Computer-readable media in which such formatted data and/or instructions may be embodied include, but are not limited to, non-volatile storage media in various forms (e.g., optical, magnetic or semiconductor storage media) and carrier waves that may be used to transfer such formatted data and/or instructions through wireless, optical, or wired signaling media or any combination thereof. Examples of transfers of such formatted data and/or instructions by carrier waves include, but are not limited to, transfers (uploads, downloads, e-mail, etc.) over the internet and/or other computer networks via one or more data transfer protocols (e.g., HTTP, HTTPs, FTP, SMTP, WAP, etc.). Such data-and/or instruction-based expressions of the components described above may be processed by a processing entity (e.g., one or more processors) within a computer system in connection with the execution of one or more other computer programs when received within the computer system via one or more computer-readable media.

Unless the context clearly requires otherwise, throughout the description and the claims, the words "comprise" and "comprising" are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, the words "include", "including", and the like are to be construed in a sense including, but not limited to ". Words using the singular or plural number also include the plural or singular number, respectively. Additionally, the words "herein," "hereinafter," "above," "below," and words of similar import, when used in this application, refer to this application as a whole and not to any particular portions of this application. When the word "or" is used in a list referring to two or more items, the word covers all of the following interpretations of the word: any one of the items in the list, all of the items in the list, and any combination of the items in the list.

The above description of embodiments of the system and method is not intended to be exhaustive or to limit the system and method to the precise form disclosed. While specific embodiments of, and examples for, the systems and methods are described herein for illustrative purposes, various equivalent modifications are possible within the scope of the systems and methods, as those skilled in the relevant art will recognize. The techniques of the systems and methods provided herein may be applied not only to the systems and methods described above, but to other systems and methods as well. The elements and acts of the various embodiments described above can be combined to provide further embodiments. These and other changes can be made to the systems and methods in light of the above detailed description.

In general, in the following claims, the terms used should not be construed to limit the systems and methods to the specific embodiments disclosed in the specification and the claims, but should be construed to include all systems and methods that operate under the claims. Accordingly, the present disclosure is not limited to systems and methods, but instead is to be determined entirely by the claims. While certain aspects of the systems and methods are presented below in certain claim forms, the inventors contemplate the various aspects of the systems and methods in any number of claim forms. Accordingly, the inventors reserve the right to add additional claims after filing the application to pursue such additional claim forms for other aspects of the system and method.

Claims (82)

1. A positioning system, comprising:

a terrestrial transmitter network comprising a plurality of transmitters that broadcast a positioning signal comprising at least a ranging signal and positioning system information, wherein a ranging signal comprises information for measuring a distance to a transmitter broadcasting the ranging signal;

a reference sensor array comprising at least one reference sensor cell located at a known location;

a remote receiver comprising an atmospheric sensor that collects atmospheric data at a location of the remote receiver; and

a positioning application running on a processor and coupled to the remote receiver,

wherein the positioning application generates an equivalent reference altitude pressure at the location of the remote receiver using the atmospheric data and reference data from a set of reference sensor units of the reference sensor array,

wherein a pressure surface gradient model uses the reference data from the set of reference sensor units to generate an equivalent reference elevation pressure at the location of the remote receiver,

wherein the positioning application calculates the position of the remote receiver using an equivalent reference altitude pressure at the position of the remote receiver and information derived from the positioning signal, an

Wherein the location comprises an altitude.

2. The location system of claim 1, wherein the remote receiver operates in a reduced power state when the location signal is at least one of undetected and unusable.

3. The location system of claim 2, wherein the remote receiver determines a position using a set of location signals from a set of transmitters of the plurality of transmitters, wherein the remote receiver operates in a reduced power state when the set of location signals is at least one of undetected and unusable.

4. The positioning system of claim 3, wherein the remote receiver transitions from the reduced power state to a full power state in response to detecting at least one of a motion of the remote receiver, a change in position of the remote receiver, and a change in signal conditions of the positioning signal.

5. The location system of claim 1, comprising a server coupled to the remote receiver, wherein the location application resides on the server and the server calculates the location.

6. The location system of claim 1, comprising a server coupled to the remote receiver, wherein the location application resides on the remote receiver and the server.

7. The location system of claim 1, wherein the first mode of operation of the remote receiver comprises a terminal-based location at which the remote receiver calculates the location, and wherein the second mode of operation of the remote receiver comprises a network-based location at which a server calculates the location.

8. The location system of claim 1, wherein the location application resides on the remote receiver and the remote receiver calculates the location.

9. The positioning system of claim 1, wherein the known location is a location of a group of transmitters of the plurality of transmitters.

10. The positioning system of claim 1, wherein the positioning application generates an equivalent reference altitude pressure for each reference sensor unit in the set of reference sensor units using the reference data from that reference sensor unit.

11. The positioning system of claim 10, wherein the reference data includes pressure, temperature, and location data of the reference sensor unit, and wherein the location data of the reference sensor unit includes an altitude of the reference sensor unit.

12. The positioning system of claim 11, wherein the positioning application generates the equivalent reference altitude pressure at the location of the remote receiver using the equivalent reference altitude pressure for each reference sensor unit in the set of reference sensor units and the latitude and longitude of the remote receiver.

13. The positioning system of claim 12, wherein the positioning application generates the altitude of the remote receiver using the atmospheric data and the equivalent reference altitude pressure at the location of the remote receiver.

14. The positioning system of claim 1, wherein the at least one reference sensor unit comprises a plurality of reference sensor units, wherein a first group of the plurality of transmitters is assigned to a first group of the plurality of reference sensor units and a second group of the plurality of reference sensor units is at a location different from locations of the plurality of transmitters.

15. The positioning system of claim 1, wherein the at least one reference sensor unit is assigned at least one of the plurality of transmitters.

16. The positioning system of claim 1, wherein the at least one reference sensor unit is at a location different from locations of the plurality of transmitters.

17. The positioning system of claim 1, wherein the atmospheric sensor collects pressure data and temperature data at a location of the remote receiver, wherein the remote receiver detects a rate of change of the pressure data, and wherein the positioning application uses the rate of change to determine a vertical velocity of the remote receiver.

18. The positioning system of claim 1, wherein each reference sensor unit comprises at least one atmospheric reference sensor that collects reference pressure data and reference temperature data at known locations of the atmospheric reference unit.

19. The positioning system of claim 18, wherein the atmospheric reference sensor filters the reference pressure data and reference temperature data.

20. The positioning system of claim 19, wherein the atmospheric reference sensor filters the reference pressure data and reference temperature data using an adaptive time scale.

21. The positioning system of claim 1, wherein the reference sensor array broadcasts differential data of the reference data.

22. The positioning system of claim 21, wherein the differential data is derived relative to at least one constant value.

23. The positioning system of claim 21, wherein the differential data comprises differential pressure data derived as an offset value of standard atmospheric pressure.

24. The positioning system of claim 1, wherein the reference data comprises a confidence level.

25. The positioning system of claim 1, wherein each reference sensor unit processes the reference data of that reference sensor unit and determines an equivalent reference altitude pressure of the reference sensor unit.

26. The positioning system of claim 1, wherein the reference data comprises a location of each reference sensor unit in the reference sensor array.

27. The positioning system of claim 1, wherein the at least one reference sensor unit comprises at least one local reference sensor unit that is local to at least one of a location and a structure.

28. The positioning system of claim 27, wherein the reference data comprises data of the at least one local reference sensor unit.

29. The positioning system of claim 1, wherein the atmospheric sensor of the remote receiver is automatically calibrated using the aggregated reference data over a specified time period.

30. The positioning system of claim 29, wherein the aggregated reference data is generated by discerning when the remote receiver is at a known location, accumulating deviations of the atmospheric data corresponding to the known location, and generating a corrected calibration from the accumulated deviations.

31. The positioning system of claim 1, wherein the atmospheric sensor of the remote receiver is automatically calibrated when an altitude and an atmospheric pressure of a location of the remote receiver are known.

32. The positioning system of claim 31, wherein the position of the remote receiver is determined using satellite signals.

33. The positioning system of claim 1, wherein the altitude is determined using a reference altitude that minimizes an altitude difference between altitudes calculated using at least one of the atmospheric data and the reference data, wherein the reference altitude comprises an average altitude of the atmospheric reference unit.

34. The positioning system of claim 1, wherein the altitude is determined using a reference altitude that minimizes an altitude difference between altitudes calculated using at least one of the atmospheric data and the reference data, wherein the reference altitude comprises an average altitude of an area in which the remote receiver is located.

35. The positioning system of claim 1, wherein the altitude comprises an estimated altitude derived using local limit data.

36. The positioning system of claim 35, wherein the local limit data comprises terrain data of terrain in the vicinity of the location of the remote receiver.

37. The positioning system of claim 35, wherein the local limit data includes a height of at least one structure near a location of the remote receiver.

38. The positioning system of claim 35, wherein the local limit data comprises an altitude of at least one other remote receiver in proximity to a location of the remote receiver.

39. The positioning system of claim 35, wherein the positioning application determines the altitude using the atmospheric data, the baseline data, and the local limit data.

40. The positioning system of claim 1, comprising a database coupled to the positioning application, wherein the database comprises historical data measured during a period of time, wherein the historical data comprises the reference data of the reference sensor array and atmospheric data of a plurality of remote receivers.

41. The location system of claim 40, wherein the location application determines the altitude using the historical data.

42. The positioning system of claim 40, wherein the positioning system uses the historical data to optimize the at least one reference sensor unit of the reference sensor array.

43. The positioning system of claim 1, wherein the altitude is determined by relaxing an assumption of a constant equivalent reference altitude pressure between a reference location of a reference sensor unit and a current position of the remote receiver.

44. The positioning system of claim 43, wherein the positioning system:

converting a first equivalent reference altitude pressure at the reference location to a second equivalent reference altitude pressure at a standard temperature;

determining a local temperature at the current location and converting the second equivalent reference altitude pressure to a third equivalent reference altitude pressure using the local temperature; and

determining an altitude at the current location using the third equivalent reference altitude pressure.

45. The positioning system of claim 43, wherein the positioning system:

determining a change in equivalent reference altitude pressure relative to a horizontal location using reference data at each reference sensor unit in the set of reference sensor units; and

determining a best estimate of a reference altitude pressure at the current location by combining the equivalent reference altitude pressures of the set of reference sensor units.

46. The positioning system of claim 45, wherein the positioning system uses a weighted averaging technique to determine the best estimate of equivalent reference altitude pressure, wherein the weight is a function of the horizontal distance between the location of the reference sensor unit and the current position.

47. The positioning system of claim 45, wherein the positioning system determines the best estimate of equivalent reference altitude pressure by: using a least squares fit to create a second order surface that best fits the calculated sea level pressure at each reference sensor cell of the set of reference sensor cells; and interpolating the best estimate of the equivalent reference altitude pressure at the current location using an nth order surface.

48. The positioning system of claim 43, wherein the positioning system:

converting the first equivalent reference altitude pressure at each reference sensor unit of the set of reference sensor units to a second equivalent reference altitude pressure at a standard temperature; and

determining a best estimate of the equivalent reference altitude pressure at the current location by combining the second equivalent reference altitude pressures from each reference cell.

49. The positioning system of claim 48, wherein the positioning system uses a weighted averaging technique to determine the best estimate of equivalent reference altitude pressure, wherein the weight is a function of the horizontal distance between the location of the reference sensor unit and the current location.

50. The positioning system of claim 48, wherein the positioning system determines the best estimate of equivalent reference altitude pressure by: using a least squares fit to create a second order surface that best fits the calculated equivalent reference altitude pressure at each reference sensor unit in the set of reference sensor units; and interpolating the best estimate of sea level pressure at the current location using an nth order surface.

51. The positioning system of claim 1, wherein the remote receiver comprises a correlator that correlates the received signal with a pseudorandom code.

52. The positioning system of claim 51, wherein the correlator comprises a first shift register comprising a series of sets of second shift registers having parallel random access reading capability.

53. The positioning system of claim 52, wherein each of the sets of second shift registers comprises a plurality of shift register bank cells in series.

54. The location system of claim 53, wherein each shift register bank cell comprises an n-bit shift register bank cell.

55. The positioning system of claim 54, wherein each shift register bank cell comprises a 16-bit shift register bank cell.

56. The positioning system of claim 53, wherein each set of second shift registers forms a 32-bit shift register.

57. The positioning system of claim 53, wherein the series of sets of second shift registers comprises a plurality of sets of n-bit shift registers.

58. The positioning system of claim 57, wherein the series of sets of second shift registers comprises 32 sets of second shift registers, wherein the first shift register is a 1024-bit shift register.

59. The positioning system of claim 58, wherein the shifting operation of the first shift register occurs at a clock rate of a clock coupled to the correlator.

60. The positioning system of claim 59, wherein the read out operation of the first shift register occurs at a speed at least twice the clock rate.

61. The positioning system of claim 60, wherein the read out operation of the first shift register occurs at a rate that is 32 times the clock rate.

62. The positioning system of claim 57, comprising a plurality of adders in series coupled to outputs of the series of sets of second shift registers.

63. The location system of claim 62, wherein the series of a plurality of adders comprises an adder tree, wherein the adder tree includes adder cells of wider bit width.

64. The positioning system of claim 62, wherein the series of plurality of adders comprises an adder coupled to each of the plurality of sets of n-bit shift registers.

65. The positioning system of claim 64, wherein the series of the plurality of adders includes a first adder coupled to outputs of the first plurality of sets of second shift registers, a second adder coupled to outputs of the second plurality of sets of second shift registers, a third adder coupled to outputs of the third plurality of sets of second shift registers, and a fourth adder coupled to outputs of the fourth plurality of sets of second shift registers.

66. The location system of claim 62, comprising an end summer coupled to outputs of the series of multiple summers.

67. The positioning system of claim 66, comprising: aligning outputs of the series of the plurality of adders in the series of the plurality of groups of the end adders.

68. The positioning system of claim 67, wherein, in the end adders, the output of a first adder is aligned in a first group, the output of a second adder is aligned in a second group, the output of a third adder is aligned in a third group, and the output of a fourth adder is aligned in a fourth group.

69. The positioning system of claim 67, wherein the end summer forms a sum by summing the contents of the plurality of groups in series.

70. The location system of claim 1, wherein the remote receiver operates in a reduced power state when the location signal is not detected.

71. The location system of claim 1, wherein a location application resides on the remote receiver and the remote receiver calculates the location.

72. The location system of claim 1, wherein the remote receiver operates in a reduced power state when the location signal is at least one of undetected and unavailable.

73. The location system of claim 1, wherein the remote receiver determines the location using a set of location signals from a set of the plurality of transmitters, wherein the remote receiver operates in a reduced power state when the set of location signals is at least one of undetected and unavailable.

74. The positioning system of claim 1, wherein the remote receiver transitions from a reduced power state to a full power state in response to detecting at least one of a motion of the remote receiver, a change in position of the remote receiver, and a change in signal conditions of the positioning signal.

75. The location system of claim 1, wherein the remote receiver comprises a high speed clock.

76. The positioning system of claim 75, wherein the remote receiver receives pulse edges from a common time reference, wherein the remote receiver uses the high speed clock to determine a time difference between an occurrence of the pulse edges and a rising edge of a sample clock.

77. The positioning system of claim 76, wherein the remote receiver applies a correction to an estimated range based on the time difference, wherein the correction improves an accuracy of the estimated range.

78. The positioning system of claim 1, wherein the remote receiver temporarily uses a local receive chain of a plurality of local receive chains of the remote receiver to acquire at least one of the positioning signal and a satellite signal.

79. The location system of claim 78, wherein the plurality of local receive chains includes a diversity receive chain that improves receive diversity.

80. The positioning system of claim 79, wherein the remote receiver comprises a wide bandwidth receiver.

81. The location system of claim 80, wherein the remote receiver comprises a wide bandwidth cellular band receiver.

82. The positioning system of claim 79, wherein the remote receiver uses the diversity receive chain at least one of temporarily and permanently to acquire the positioning signal.