CN119546924A - Method for correcting the attitude provided by a dead reckoning navigation system by means of a relative positioning system - Google Patents
Method for correcting the attitude provided by a dead reckoning navigation system by means of a relative positioning system Download PDFInfo
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- CN119546924A CN119546924A CN202380052599.0A CN202380052599A CN119546924A CN 119546924 A CN119546924 A CN 119546924A CN 202380052599 A CN202380052599 A CN 202380052599A CN 119546924 A CN119546924 A CN 119546924A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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Abstract
The invention relates to a posture correction method (107) comprising estimating (116) a plurality of estimated positions of a dead reckoning navigation system (22) in an arbitrary fixed reference frame by means of the dead reckoning navigation system (22) upon determination, obtaining (114) the position of the dead reckoning navigation system (22) estimated by a relative positioning system (24) in a predetermined fixed reference frame upon determination, and inferring (124) at least one posture correction parameter by minimizing a cost function comparing the estimated positions with estimated positions corrected by means of the or each correction parameter.
Description
Technical Field
The present invention relates to dead reckoning navigation techniques, and more particularly to techniques for resetting gestures provided by dead reckoning navigation systems. It has advantageous application in the movement of urban or indoor environments (i.e. within buildings).
Background
It is now common to track the position of an object by means of a polygon by measuring the distance between a receiver attached to the object and a source of at least three positions in a known environment. This is the case, for example, of the GNSS (global navigation satellite system, such as GPS) type or of the positioning system benefiting from the infrastructure of a wireless communication network (such as Wi-Fi network, GSM network, etc.). However, these methods are very limited because they do not guarantee the availability and accuracy of the information, both of which are affected by the shielding that may exist between the source and the receiver. Thus, their use in urban or indoor environments requires the deployment of expensive infrastructure, with many sources distributed throughout the environment. They also rely on external technologies such as satellites of the GNSS, which may not be available or even be deliberately disturbed.
Alternatively, a method called a dead reckoning navigation method is also known, in which since a motion sensor measures the motion of an object, the relative position of the object can be tracked in any environment. The relative position refers to the position of the object in space with respect to a given point and coordinate system at initialization. In addition to position, these methods can also obtain the orientation (also called "pose") of the object with respect to the same initial coordinate system, which in dimension 3 is defined by the euler angle (rollPitch θ, yaw ψ), in dimension 2, given by heading ψ. These methods are preferable in the case of movement in an environment where position tracking by a polygon method is difficult (e.g., a city or an indoor environment).
Dead reckoning navigation is of different types. Most common are those known as "simple" inertial navigation, such as in heavy applications such as fighter or airliner, submarines, boats, etc. It is based on an inertial unit, typically comprising at least three accelerometers and three gyroscopes arranged in three axes. Typically, gyroscopes "hold" a coordinate system in which double time integration of accelerometer measurements makes it possible to estimate motion. It is well known that in order to use this "simple" inertial navigation method, it is necessary to use sensors of very high precision. In fact, double time integration of acceleration measurements means that a constant acceleration error will produce a position error that increases in proportion to the square of time.
Another known dead reckoning navigation technique is a technique in which velocity vector information in an object coordinate system is provided by an external source (e.g., an odometer of an automobile, a log of a ship, or a pitot tube of an aircraft). Then, the trajectory of the object can be known by simply integrating the velocity vector information and combining it with the direction information, particularly heading information, of the object. The time drift is less sensitive to the same measurement inaccuracy of the sensor.
Typically, the initial pose is known, for example by initial "alignment" of the inertial device or by power supply of a sensor other than the inertial sensor (e.g. a magnetic sensor). However, measurement inaccuracies of inertial sensors can lead to time drift of the measured pose, which makes knowledge of the initial pose obsolete after a more or less long time, depending on the accuracy of the sensor used, and to inaccuracies in the object position. For example, a 1% error in heading measurement after moving 100 meters may result in an inaccurate object position of 1 meter.
To solve this problem, it is known to periodically reset the measurement results of a dead reckoning navigation system by means of another positioning system in order to best maintain the directional information, in particular heading information, of the object. It is known, for example from WO 2019/020961, to reset direction information by using magnetic heading measurements obtained by magnetometers carried by an object.
However, this solution is not entirely satisfactory. In fact, magnetometers have their own inaccuracy and drift, which means that their measurements are sometimes not reliable enough to be used as a basis for a reset. Furthermore, this solution requires integrating magnetometers into the object whose position is to be tracked, which increases its cost.
Disclosure of Invention
It is an object of the present invention to propose a simple and economical solution for resetting the attitude provided by a dead reckoning navigation system. Another object is to allow such a reset to be performed with a high accuracy within a short distance. Another object is to accurately track people moving inside a building in a simple and economical manner.
To this end, according to a first aspect, the present invention relates to a pose resetting method for resetting a pose provided by a dead reckoning navigation system, the resetting method comprising the steps of:
estimating, by the dead reckoning navigation system, an estimated position of the dead reckoning navigation system in an arbitrary fixed coordinate system at each of a plurality of determined times included in a movement interval in which the dead reckoning navigation system moves along a movement trajectory,
-For each determined instant, obtaining an estimated position of the dead reckoning navigation system in a predetermined fixed coordinate system at said determined instant, said estimated position having been estimated by the relative positioning system, and
-Deducing at least one pose reset parameter by minimizing a cost function comparing the estimated position with the estimated position corrected by means of the or each reset parameter.
According to a particular embodiment of the invention, the pose resetting method also has one or more of the following features, alone or in any technically possible combination:
-the dead reckoning navigation system is worn by the pedestrian, the dead reckoning navigation system preferably being attached to the foot or ankle of the pedestrian;
the dead reckoning navigation system comprises a motion sensor for measuring the motion of the dead reckoning navigation system and a processing unit for pushing off the pose and position of the dead reckoning navigation system from the measured motion;
The relative positioning system is selected from the group consisting of a multi-angle system, a multilateral system, a map matching system and a visual positioning system, the relative positioning system preferably comprising an ultra wideband telemetry device;
-any fixed coordinate system and a predetermined fixed coordinate system share a common axis, the posture reset parameter being constituted by a parameter (preferably angle) modifying the direction by rotation around said common axis;
-the common axis is the vertical axis;
The cost function represents the average geometrical deviation between the estimated position and the estimated position after applying a geometrical transformation comprising rotation and preferably translation to the estimated position or the estimated position;
-rotating about an axis of rotation and translating in a direction orthogonal to said axis of rotation;
-the step of inferring a reset parameter comprises calculating a candidate value for the reset parameter, evaluating an accuracy value of the candidate value, comparing the accuracy value with a previous accuracy value associated with a previous reset parameter, and determining the reset parameter based on the comparison result, the reset parameter being dependent on the candidate value and the previous reset parameter.
The precision value is a function of the estimated position and the uncertainty in the estimated position and/or the average geometrical deviation between the estimated position and the estimated position after application of the candidate value of the reset parameter.
-Inferring the reset parameter comprises the sub-steps of:
o a) calculating a first candidate value of the reset parameter by minimizing a cost function that compares estimated positions at N determined instants with estimated positions at said N determined instants corrected by means of the reset parameter,
O b) calculate a first precision value associated with the first candidate value,
O c) calculating a second candidate value of the reset parameter by minimizing a cost function comparing estimated positions of N-1 determined instants corresponding to the N determined instants minus the oldest determined instant with estimated positions of the N-1 determined instants corrected by means of the or each reset parameter,
O d) calculate a second precision value associated with the second candidate value,
O e) comparing the first precision value with the second precision value, and
O f) selecting a first candidate value when the first precision value reflects the best precision;
-when the precision value reflecting the best precision consists of the second precision value, inferring the reset parameter comprises the following additional sub-steps:
o delete the estimated position and estimated position at the oldest determined instant, and
O repeating sub-steps a) to e), wherein the number N is reduced by 1, and
Dead reckoning navigation systems have an accuracy of about a few percent in terms of distance travelled, for example between 1% and 3%
The accuracy in terms of heading drift is in the order of tens of degrees per hour, for example between 30 and 80 degrees per hour, and the accuracy in position of the relative positioning system is in the order of tens of centimeters, for example between 20cm and 1 m.
According to a second aspect, the invention also relates to a method for locating an object in a predefined space, the method comprising the steps of:
-starting up a dead reckoning navigation system,
Resetting the pose of a dead reckoning navigation system using a relative positioning system comprising an infrastructure installed at an access point of a predefined space to obtain pose reset parameters, said pose reset implementing the pose reset method according to any of the preceding claims,
Resetting the position of a dead reckoning navigation system using a relative positioning system comprising an infrastructure installed at said access point of a predefined space to obtain a position resetting parameter, and
-Calculating by the dead reckoning navigation system a calculated position of the dead reckoning navigation system in a predetermined coordinate system by means of the pose reset parameter and the position reset parameter.
According to a particular embodiment of the invention, the positioning method has the following further features:
The infrastructure is loaded on a vehicle, which is itself equipped with a positioning and orientation system, so that the position of the infrastructure in a predetermined coordinate system can be calculated.
According to a third aspect, the invention also relates to a dead reckoning navigation system comprising a motion sensor for measuring the motion of the dead reckoning navigation system and a processing unit for pushing off the pose and position of the dead reckoning navigation system in a fixed coordinate system from the measured motion, the processing unit being configured to implement the pose resetting method according to the first aspect to reset the pose.
According to a fourth aspect, the invention relates to a computer program product comprising code instructions for performing the pose resetting method according to the first aspect when said program is executed by a processor.
Finally, according to a fifth aspect, the present invention relates to a storage device readable by a computer apparatus, having recorded thereon a computer program product comprising code instructions for performing the pose resetting method according to the first aspect.
Drawings
Other features and advantages of the invention will appear upon reading the following description, given by way of example only, with reference to the accompanying drawings in which:
figure 1 is a top view of a system for positioning objects in a predefined space according to an exemplary embodiment of the invention,
Figure 2 is a perspective view of a detail of the positioning system of figure 1,
Figure 3 is a schematic view of a positioning box of the positioning system of figure 1,
Figure 4 is a schematic diagram illustrating one example of a method implemented by the system of figure 1 for positioning an object in a predefined space,
FIG. 5 is a schematic diagram showing the course reset step of the method of FIG. 4, and
FIG. 6 is a schematic diagram showing the sub-steps of inferring the heading reset parameters of the heading reset step of FIG. 5.
Detailed Description
The positioning system 10 shown in fig. 1 is intended to position an object of interest 12 within a predefined space 14. To this end, the localization system 10 includes a plurality of localization boxes 16, each localization box 16 being attached to a respective object of interest 12. Here, the positioning system 10 further comprises a positioning infrastructure 18 arranged at least at one access point 19 of the predefined space 14.
Referring to fig. 2, each object of interest 12 herein is comprised of a pedestrian. The present invention is particularly advantageous in this application because it allows for a substantial reduction in the volume of the case 16, so that a pedestrian can easily ergonomically wear the case 16. As a variant (not shown), the object of interest 12 consists of any moving object requiring knowledge of position, such as a wheeled vehicle, a drone, etc.
The predefined space 14 is typically constituted by the interior of a building. For example, if it is an industrial location, the pedestrian 12 is typically a technician working at the industrial location. As a variant, if the predefined space 14 is an intervention site, such as a building on fire or a man-in-the-ground event, the pedestrian 12 is a firefighter or an infantry intervening in the site.
Each localiser box 16 is typically attached to a limb, here a leg, preferably a foot or ankle, of the pedestrian 12. To this end, as shown in fig. 3, each positioning box 16 comprises an attachment member 20, here constituted by a bracelet, for example with a shackle strip encircling the limb and allowing a firm connection. As a variant (not shown), the attachment member 20 is constituted by any element that allows connection with the object of interest 12 fixed to the localization box 16.
Still referring to fig. 3, the localization box 12 includes a dead reckoning navigation system 22. It also includes a relative positioning system 24. In the example shown, it also includes a communication system 26, typically a wireless communication system, for communication of the position box 12 with external devices, such as a mobile terminal 29 (fig. 2), for example a multifunction mobile device, or even a remote server (not shown). Optionally, it includes a storage module 28.
The dead reckoning navigation system 22 includes a motion sensor 30 for measuring motion of the dead reckoning navigation system 22 and a processing unit 32 for pushing the pose and position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system, such as the East-North-Up (ENU) coordinate system, from the measured motion. By "fixed coordinate system" is meant herein and hereinafter that the coordinate system is stationary in the earth reference frame.
In the example described herein, the dead reckoning navigation system 22 is configured to operate in a two-dimensional coordinate system and only provide the heading and two position coordinates of the dead reckoning navigation system 22 in the horizontal plane of the predetermined coordinate system. As a variation (not shown), the dead reckoning navigation system 22 is configured to operate in a three-dimensional coordinate system and thus provide the roll, pitch and yaw angles of the dead reckoning navigation system 22, as well as its three position coordinates in a predetermined coordinate system. Those skilled in the art will be readily able to convert the examples given herein for the two-dimensional case into the three-dimensional case.
The motion sensor 30 comprises a gyroscope 40 for measuring the angular velocity of the dead reckoning navigation system 22 from a system having three orthogonal axes defining a moving coordinate system fixed to the box 16, i.e. measuring three components of the angular velocity vector in said moving coordinate system. Thus, it will be appreciated that gyroscope 40 may actually specify a set of three gyroscopes associated with one of the three axes, particularly in three axes (i.e., each gyroscope is capable of measuring one of the three components of the angular velocity vector).
The motion sensor 30 further includes means 42 for acquiring a linear velocity of the dead reckoning navigation system 22 (i.e., a linear velocity of motion). The acquisition member 42 makes it possible to obtain the linear velocity directly or indirectly, and thus may be of various types.
For example, acquisition member 42 may be comprised of one or more accelerometers (not shown). These accelerometers are advantageously arranged on three axes, typically according to the same system as gyroscope 40 with three orthogonal axes. They are sensitive to external forces other than gravity applied to the sensor 30 and can measure specific accelerations. The linear velocity is then obtained by time integrating the acceleration.
As a variant, when object 12 is a wheeled vehicle, acquisition member 42 is composed of at least two odometers, one for each wheel of the vehicle, for example two rear wheels. Odometers refer to devices capable of measuring wheel speed by counting revolutions ("tachometers"). Typically, an odometer has a component (e.g. a magnet) fixed to the wheel and detects each pass of this fixed component (called "top") in order to count the revolutions per unit time, i.e. the rotation frequency. Other techniques are known, such as optical detection of the imprint on the wheel, or the magnetometer of patent FR2 939 514, which detects the rotation of a metal object, such as a wheel. Here, the "speed" of the wheel is a scalar, i.e. the wheel's velocity norm in the earth reference frame (assuming no slip). This velocity norm can be estimated by measuring the rotational frequency if the spokes of the wheel are known.
Optionally, the motion sensor 30 also includes a stride detector (not shown) to detect when the foot of the pedestrian 12 is on the ground, as described in document WO 2017/060660, for example.
In the example shown, the processing unit 32 is constituted by a programmable machine, such as a DSP (digital signal processor) or a microcontroller. It comprises a processor or CPU (central processing unit) 44 and a memory 46 of the RAM (random access memory) and/or ROM (read only memory) type. The processor 44 is configured to execute instructions loaded into the memory 46. When the dead reckoning navigation system 22 is powered on, the processor 44 is able to read instructions from the memory 46 and execute them. These instructions form a computer program that causes the processor 44 to calculate the heading and position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system, such as by implementing the methods described in WO 2017/060660 or FR 2 939 514.
As a variant (not shown), the processing unit 32 is constituted by a dedicated machine or component, such as an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).
The processing unit 32 also includes a buffer memory 49 for temporarily storing information needed to calculate the heading position and location of the dead reckoning navigation system 22 in a predetermined fixed coordinate system.
Optionally, the dead reckoning navigation system 22 also includes a network of magnetometers 48 linked to the pod 16, i.e., each having substantially the same motion in the earth reference frame as the pod 16 and spatially spaced apart from each other. Each magnetometer 48 is a three-axis magnetometer capable of measuring magnetic fields along three axes. To this end, each magnetometer 48 is typically comprised of three single axis magnetometers (not shown) oriented along axes that are substantially perpendicular to one another. These axes are preferably the same as the axes of a system with three orthogonal axes of gyroscope 40.
Due to its specific geometry, the network of magnetometers 48 is able to authorize the determination of the spatial gradient of the measured magnetic field at each measurement instant of magnetometer 48, in particular the coefficients of this gradient along each axis of the mobile coordinate system linked to cassette 16. Each coefficient of the gradient is determined, for example, by a method of vector measurement of the magnetic field using magnetometer 48, associated with a least squares or median filter type optimization method, or with the inherent characteristics of the magnetic field described by maxwell's equations. However, any other conventional method suitable for calculating the spatial gradient coefficients of the magnetic field is suitable.
The processing unit 32 is then typically configured to adjust the determination of the velocity of the dead reckoning navigation system 22 by implementing the method described in EP2 541 199.
The dead reckoning navigation system 22 typically has an accuracy in terms of distance traveled of about a few percent, such as between 1% and 3%, and a accuracy in terms of dead reckoning drift of about tens of degrees per hour, such as between 30 and 80 degrees per hour.
The relative positioning system 24 is capable of identifying the relative position of a point fixed to the dead reckoning navigation system 22 with respect to a reference frame having a known position in a predetermined fixed coordinate system and is capable of deriving therefrom the position of the dead reckoning navigation system 22 in the predetermined fixed coordinate system. To this end, the relative positioning system 24 comprises a sensor 50 capable of measuring a parameter that enables positioning of the safety point relative to the reference frame, and a processing unit 52 for inferring from the parameter the position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system.
Preferably, the relative positioning system 24 is constituted by a polygonal system, in particular by a contiguous polygonal system. The infrastructure 18 then includes at least three beacons 54 (fig. 2) (or "anchors") at the or each access point 19, each beacon having a known location in a predetermined fixed coordinate system, and the relative positioning system 24 is configured to communicate therewith. To this end, the sensor 50 is typically comprised of a wireless communication system capable of communicating with the beacons 54 and inferring the distance to each beacon 54, for example, by measuring two-way ranging (TWR) distances.
Preferably, the sensor 50 is constituted by an ultra wideband telemetry device capable of communicating with the beacon 54 and measuring its distance from the beacon 54 via an Ultra Wideband (UWB) protocol, which allows measurement accuracy of locations on the order of 10 centimeters, typically between 20cm and 1 m. As known to those skilled in the art, ultra wideband protocols are based on radio communication protocols that transmit very short pulses (on the order of nanoseconds) over a broad spectrum. Thus, depending on the channel used, communications benefit from a wide bandwidth (500 MHz to 1350 MHz) in the range of 0.5GHz to 9.5GHz (center frequency). Alternatively, the sensor 50 can communicate with the beacon 54 via the Bluetooth protocol or Wi-Fi protocol.
As a variant, the multilateral system is constituted by a GNSS system.
The processing unit 52 is then configured to infer, typically by multilateration or by optimization, the relative position of the sensor 50 in the predetermined fixed coordinate system from the distance measurements of the beacons 54 and the known position, and to infer the position of the dead reckoning navigation system 22 in the predetermined fixed coordinate system from the position and from the position of the sensor 50 relative to the dead reckoning navigation system 22.
According to another embodiment (not shown), the relative positioning system 24 is constituted by a multi-angle system, the sensor 50 being able to measure at least one angle between the directions of view of two beacons, each having a known position in a predetermined fixed coordinate system. The processing unit 52 is then configured to infer the position of the sensor 50 in the predetermined fixed coordinate system from the one or more angle measurements and from the known position of the beacon 54, typically through multiple angles, and to infer the position of the dead reckoning navigation system 22 in the predetermined fixed coordinate system from the position and from the position of the sensor 50 relative to the dead reckoning navigation system 22.
According to yet another embodiment (not shown), the relative positioning system 24 is constituted by a map matching system. The sensor 50 can then measure a parameter of the environment, such as a topography or a magnetic field, and the processing unit 52 can match the measurement with a map of said parameter stored in its memory in order to deduce therefrom the position of the sensor 50 in a predetermined fixed coordinate system.
According to a fourth embodiment (not shown), the relative positioning system 24 is constituted by a visual positioning system. The sensor 50 is then formed by an imager associated with the image processing system. The imager is configured to acquire images of the environment and the processing system to detect salient points, such as lines of sight, in each image, the locations of which are known in a predetermined fixed coordinate system. The processing unit 52 is then configured to infer therefrom the relative position of the sensor with respect to the salient point and the position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system from the relative position and from the known position of the salient point and the position of the sensor 50 with respect to the dead reckoning navigation system 22.
As a variant (not shown), the imager is stationary (it belongs to the infrastructure 18) and it is a point of significance (typically a line of sight) carried by the cassette 16. As another variation, a motion capture configuration may be provided in which multiple targets are carried by the cassette 16 and detected by a stationary imager.
In the example shown, the processing unit 52 is constituted by a programmable machine, such as a DSP (digital signal processor) or a microcontroller. It comprises a processor or CPU (central processing unit) 56 and a memory 58 of the RAM (random access memory) and/or ROM (read only memory) type. The processor 56 is configured to execute instructions loaded into the memory 58. When the relative positioning system 24 is powered on, the processor 56 is able to read instructions from the memory 58 and execute them. These instructions form a computer program that causes the processor 56 to calculate the position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system based on the parameters measured by the sensor 50.
As a variant (not shown), the processing unit 52 is constituted by a machine or a dedicated component, such as an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit).
In the illustrated example, the processing unit 52 of the relative positioning system 24 is different than the processing unit 32 of the dead reckoning navigation system 22. As a variant (not shown), these processing units 32, 52 are combined.
The communication system 26 is configured to enable short range wireless communications, such as bluetooth or Wi-Fi (particularly in one embodiment with a mobile terminal 29) and/or connect to a mobile network (typically UMTS/LTE/5G) for long range communications. As a variant (not shown), the communication system 26 is for example a wired connector technology (typically USB) for transferring data from the memory module 28 to another memory module, typically a mobile terminal 29.
For example, the communication system 26 is configured to transmit the position calculated by the dead reckoning navigation system 22 to the mobile terminal 29 so that the mobile terminal 29 displays the position in the interface of the navigation software.
In the above example, the processing units 32, 52 of the dead reckoning navigation system 22 and the relative positioning system 24 are integrated into the box 16. As a variant (not shown), at least a part of these processing units 32, 52 is moved, for example in the mobile terminal 29, the infrastructure 18 and/or a remote server (not shown). In other words, at least a portion of the step of calculating the position of the dead reckoning navigation system 22 by the dead reckoning navigation system 22 or by the relative positioning system 24 is performed by the mobile terminal 29, the infrastructure 18, and/or a remote server. Communication system 26 is then configured to transmit data from motion sensor 30 and/or sensor 50 to mobile terminal 29, infrastructure 18, and/or a remote server. Advantageously, the communication system 26 is also configured to receive from the mobile terminal 29, the infrastructure 18, and/or the remote server the position of the dead reckoning navigation system 22 calculated by the dead reckoning navigation system 22 or by the relative positioning system 24.
Returning to fig. 1 and 2, as described above, the infrastructure 18 includes a plurality of beacons 54 disposed at the access points 19 of the predefined space 14. These beacons 54 are typically grouped within portals disposed at access point 19, such as portal 60 shown in fig. 2. Each portal 60 includes at least three beacons 54 to allow pedestrians 12 to be localized through the access point 19 by multiple sides.
Infrastructure 18 is, for example, a permanently fixed infrastructure. This is especially true when the predefined space 14 is an industrial location and the positioning system 10 is intended to track movements of technicians at the location. As a variant, the architecture 18 is a temporary fixed infrastructure. For example, when the predefined space 14 is an intervention site, particularly in the event of a fire, the infrastructure 18 is brought to an access point of the intervention site and installed before the arrival of the firefighter. Again as a variant, the infrastructure 18 is a mobile infrastructure. It is typically loaded on a vehicle (not shown) for transporting the pedestrian 12, the movement of the pedestrian 12 to the predefined space 14 being tracked. The vehicle itself is then equipped with a positioning and orientation system so that the position of the infrastructure 18 in a predetermined coordinate system can be calculated. This is the case, for example, when the predefined space 14 is an intervention site, in particular in the case of a man-made hijack.
The method 100 implemented by the positioning system 10, and more particularly by the processing units 32, 52, will now be described with reference to fig. 4-6.
As shown in fig. 4, the method 100 begins with a first step 102 of starting the dead reckoning positioning system 22. This first step 102 is typically performed while the pedestrian 12 wearing the box 16 is still outside the predefined space 14. Typically, step 102 is triggered by the pedestrian 12 pressing a button (not shown) on the box 16. The relative positioning system 24 generally begins at the same time as step 102.
After it is initiated, the dead reckoning positioning system 22 provides the position of the pedestrian 12 in any fixed coordinate systemThe position v (t) is affected by random errors. For simplicity, the random error is here assimilated as a central Gaussian variance variableFor further simplification, it is then assumed that there is no spatial correlation between the directions of the planes, i.e. the terms Covar (v 1,v2) and Covar (v 2,v1) are zero. For simplicity, the terms Var (v 1) and Var (v 2) are considered to be equal below, so the variance Γ v can be written asWhere σ v (t) reflects the uncertainty of the position v (t), I 2 is an identity matrix of dimension 2. If this uncertainty σ v (t) is a priori variable that varies over time, the magnitude of this variation is typically low. Thus, a constant uncertainty σ v is considered here and below.
The dead reckoning positioning system 22 also provides the heading ψ (t) of the pedestrian 12 in the arbitrary fixed coordinate system. This arbitrary fixed coordinate system is a two-dimensional horizontal coordinate system, which generally consists of a translation of a predetermined fixed coordinate system by an angle of rotation θ and a horizontal vector Δ about a vertical axis. Thus, any fixed coordinate system shares a common axis with a predetermined fixed coordinate system constituted by a vertical axis. Which is arbitrarily selected by the dead reckoning positioning system 22 based on the direction in which it was started.
The relative positioning system 24 provides the horizontal position of the pedestrian 12 in a predetermined fixed coordinate system The position u (t) is affected by random errors. For simplicity, this random error is here assimilated as a central Gaussian variance variableFor further simplification, it is assumed hereinafter that there is no spatial correlation between the directions of the planes, i.e. the terms Covar (u 1,u2) and Covar (u 2,u1) are zero. For further simplicity, the terms Var (u 1) and Var (u 2) are considered to be equal below, so the variance Γ u can be written asWhere σ u (t) reflects the uncertainty of the position u (t), I 2 is an identity matrix of dimension 2. If this uncertainty σ u (t) is a priori variable that varies over time, the magnitude of this variation is typically low. Thus, a constant uncertainty σ u is considered here and below.
Step 102 is followed by step 104 for determining a likelihood that the relative positioning system 24 will evaluate the position of the dead reckoning navigation system 22 in a predetermined fixed coordinate system. If the determination is affirmative, i.e., typically if the cassette 16 is within range of the beacon 54 of the infrastructure 18, step 104 is followed by step 106 of resetting the position of the dead reckoning navigation system 22 and step 107 of resetting the heading of the dead reckoning navigation system 22. If the determination is negative, i.e., typically if the box 16 is outside the range of the beacon 54 of the infrastructure 18, then step 104 is repeated after a delay.
During the position resetting step 106, the dead reckoning navigation system 22 estimates the position v of the pedestrian 12 in any fixed coordinate system at time t 0 (t 0), while the relative positioning system 24 estimates the position u of the pedestrian in the predetermined fixed coordinate system at time t 0 (t 0), and communicates the estimated position u (t 0) to the dead reckoning navigation system 22. The dead reckoning navigation system 22 then determines a position reset parameter δ consisting of the difference between the estimated u (t 0) and the estimated v (t 0) position, Δ=v (t 0)-u(t0). The dead reckoning navigation system 22 then adjusts the estimated position by applying the position reset parameter Δ:
referring to fig. 5, when the box 16 is within range of the beacon 54 of the infrastructure 18, a heading reset 107 begins with the pedestrian 12 following a movement 110 of the movement track within the movement interval.
During this movement 110, for a plurality of evaluation moments i k included in the movement interval, the heading reset 107 includes an evaluation 112 of the position u (i k) of the pedestrian 12 in a predetermined fixed coordinate system by the relative positioning system 24 at said evaluation moment i k. After the evaluation 112, the dead reckoning navigation system 22 receives 114 the evaluation location u (i k).
Meanwhile, for a plurality of estimated times τ k included in the movement interval, the heading reset 107 also includes an estimate 116 of the position v (τ k) of the pedestrian 12 by the dead reckoning navigation system 22 in any fixed coordinate system at the estimated time τ k.
Following the receiving step 114 and the estimating step 116 is a step 118 of matching the estimated position u (i k) and the estimated position v (τ k) of the dead reckoning navigation system 22. In practice, the resetting step 107 is based on the use of the estimated position synchronized with the estimated position. However, the two locations come from different sources, and the estimated time instant i k is typically different from the estimated time instant τ k. Thus, a match is required between the estimated u (i k) and estimated v (τ k) positions. This matching aims at correlating and synchronizing the estimated u (i k) and estimated v (τ k) positions so that at each of a plurality of determined instants t k there is a pair of estimated position u (t k) and estimated position v (t k) at said determined instant t k. Thus, this matching includes a set { u (i k)}k) from the set of positions u (i k) estimated at the estimated time instant i k and a set { v (inferred from τ k)}k:
-a set { u (t k)}k), and of positions u (t k) evaluated at a determined instant t k
-A set { v (t k)}k) of positions v (t k) estimated at a determined instant t k.
To this end, matching includes interpolating at least one set or subset, for example, among:
-a set { u (i k)}k), of positions u (i k) estimated at an estimation instant i k, and
-A set { v (τ k) } k of positions v (τ k) estimated at an estimated instant τ k.
Such interpolation preferably uses time splines. Preferably, the spline for interpolation is differentiable at least twice. Splines represent a continuity of the trajectory that may be forced in particular. Spline representation can also use a method based on the gradient of the criterion to be minimized to optimize the various parameters involved, in particular the time synchronization parameters. As a variation, interpolation uses another method, such as, for example, a discrete representation of the trajectory traveled by the pedestrian 12.
Preferably, only the set { v (τ k) } k of estimated positions is interpolated, and the determination time t k is selected to be equal to the evaluation time i k：tk＝ik. Thus, the set { u (t k)}k) of positions u (t k) estimated at the determination time t k merges with the set { u (i k)}k) of positions u (i k) estimated at the estimation time i k. Thus, the receipt 114 of the positions u (i k) estimated at the estimation time i k by the dead reckoning navigation system 22 constitutes a step of obtaining the estimated position u (t k) of the pedestrian 12 at the determination time t k by the dead reckoning navigation system 22.
As a variation, only the set of estimated positions { u (t k)}k) is interpolated, the determination time t k is selected to be equal to the estimated time τ k：tk＝τk. Thus, the matching 118 constitutes a step of obtaining the estimated position u (t k) of the pedestrian 12 by the dead reckoning navigation system 22 at the determination time t k.
It should be noted that in the case where the evaluation time i k corresponds to the evaluation time τ k, the matching 118 is limited to associating the estimated position u (i k) and the estimated position v (τ k) with the same time i k、τk, which then become the determination time t k.
After matching 118, the matched pair of locations u (t k)、v(tk) in buffer memory 49 are added 120 and then buffer memory 49 is flushed 122. The cleaning 122 includes deleting from the buffer memory 49 the pair u of positions associated with the determined instant t k no longer in the movement interval (t k)、v(tk), which is understood here as a sliding time window of predetermined duration ending at the latest evaluation instant i k or the evaluation instant τ k.
These steps 120, 122 are followed by a step 124 of inferring a heading reset parameter θ. The heading reset parameter θ is here constituted by a parameter, in particular an angle, that modifies the direction by rotation about an axis of a predetermined coordinate system (here a vertical axis). Optionally, in parallel with step 124, the heading reset 107 also includes other steps (not shown) to infer other heading reset parameters, such as parameters to correct for track angle variation bias.
Referring to FIG. 6, this step 124 includes a first substep 130 of calculating a first candidate value θ 1 for the heading reset parameter θ, where all points, i.e., all pairs of locations u, are contained in the buffer memory 49 (t k)、v(tk). The first candidate value θ 1 is calculated by minimizing a cost function that compares the estimated positions u (t k) at the N determined instants t k corresponding to the position pairs u (t k)、v(tk) included in the buffer memory 49 with the estimated positions v (t k) at the N determined instants t k corrected by means of the heading reset parameter θ and the position reset parameter Δ. The cost function particularly represents the average geometrical deviation between the estimated position { u k}k and the estimated position { v k}k after applying a geometrical transformation to the estimated position { u k}k, the geometrical transformation comprising:
-rotating an angle equal to the heading reset parameter θ about an axis of a predetermined coordinate system (here the vertical axis), and
A vector equal to the position resetting parameter delta translates in a direction orthogonal to the axis.
Thus, the cost function is equal to, for exampleWherein:
- { u k}k is the set of locations evaluated at the determined time;
- { v k}k is the set of positions estimated at the determined time instant;
- { t k}k is a set of determined instants;
-N is the number of location pairs u (t k)、v(tk) included in the buffer memory 490;
- θ is a heading reset parameter;
R (θ) is a rotation matrix representing the direction of modification by application of a heading reset parameter, and
Delta is a location reset parameter.
Thus, the first candidate value θ 1 is equal to
Wherein:
-u 1(tk) is a first position coordinate of the estimated position of the dead-reckoning navigation system 22 along a first axis of a predetermined fixed coordinate system at a determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times An average of the first position coordinates;
-u 2(tk) is the second position coordinates of the estimated position of the dead-reckoning navigation system 22 along the second axis of the predetermined fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times An average of the second position coordinates;
V 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of any fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times An average of the first position coordinates;
-v 2(tk) is the second position coordinate of the estimated position of the dead-reckoning navigation system 22 along the second axis of any fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times Average value of the second position coordinates on the first position coordinate, and
N is the number of location pairs u (t k)、v(tk) included in the buffer memory 49.
As a variant (not shown), the cost function comprises summingFor example, based on the likelihood of the term (typically the term associated with a higher variance will be given a lower weight) or the geometric distance between different terms (typically terms geometrically close to each other will be given a lower weight). As a variant, the geometric transformation is applied to the estimated position v k}k instead of the estimated position u k}k, and then the summed term is written as ||u k-R(γ)vk-Δ‖2. Still as a variant, the geometric transformation further comprises:
track smoothing parameterized by a parameter b corrected for track angle variation bias, then writing the summed term as iiv k-R(γ+b×tk)uk-Δ‖2;
And/or
Parity (homothety) parameterized by a scaling factor h, then writing the summed term as
‖vk-h×(R(θ)uk+Δ)‖2。
This sub-step 130 is followed by a sub-step 132 of evaluating a first precision value σ θ1 associated with said first candidate value θ 1. For example, the first accuracy value σ θ1 is a function of the uncertainty σ v、σu at the estimated position { v k}k and the estimated position { u k}k. It is generally composed of the standard deviation of the first candidate value θ 1 and is given by the following formula:
wherein:
- { u k}k is the set of positions evaluated at the determined moment,
- { V k}k is the set of positions estimated at the determined time instant,
- { T k}k is a set of determined instants,
-Is the variance of the random error affecting each coordinate of the position assessed by the relative positioning system 24,
-Is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22,
U 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of the predetermined fixed coordinate system at the determined time t k,
U 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of the predetermined fixed coordinate system at the determined time t k,
V 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of any fixed coordinate system at the determined time t k,
V 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of any fixed coordinate system at the determined time t k,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average value of the first position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average value of the second position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average value of the first position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAverage value of the second position coordinates, and
N is the number of location pairs u (t k)、v(tk) included in the buffer memory 49.
As a variant, the first precision value σ θ1 is a function of the average deviation observed between the set of evaluation positions { u k}k and the set of relevant evaluation positions { v k}k corrected by means of the heading reset parameter θ having the first candidate value θ 1. For example, it is given by the following formula:
Wherein the method comprises the steps of
N is the number of pairs of positions u (t k)、v(tk) included in the buffer memory 49,
- { U k}k is the set of locations evaluated at the determined time;
- { v k}k is the set of positions estimated at the determined time instant;
- is a set of dead reckoning navigation systems 22 at a determined time The average value of the estimated positions on the table,
-Is a set of dead reckoning navigation systems 22 at a determined timeAn average value of the estimated positions on the table,
- Θ 1 is a heading reset parameter giving the first candidate value θ 1, an
-R (θ 1) is a rotation matrix representing the direction modified by applying the heading reset parameter.
As a variant, the first precision value σ θ1 is a combination of a function of the uncertainty σ v、σu on the estimated positions { v k}k and { u k}k, and a function of the average deviation observed between the set of estimated positions { u k}k and the set of relevant estimated positions { v k}k corrected by means of the heading reset parameter θ having the first candidate value θ 1.
In parallel to the sub-steps 130, 132, the deducing step 124 further comprises a sub-step 134 of calculating a second candidate value θ 2 of the heading reset parameter θ without having the oldest point contained in the buffer memory 49, i.e. with all pairs of positions u (t k)、v(tk) contained in the buffer memory 49, except the pairs of positions u (t 1)、v(t1) associated with the oldest determined instant t 1. The second candidate value θ 2 is calculated by minimizing a cost function that compares the estimated position u (t k) at the N-1 determined instants t k corresponding to the latest position pair u (t k)、v(tk) included in the buffer memory 49 with the estimated position v (t k) of said N-1 determined instants t k corrected by means of the heading reset parameter θ and the position reset parameter Δ. The cost function particularly represents the average geometrical deviation between the estimated position { u k}k and the estimated position { v k}k after applying a geometrical transformation to the estimated position { u k}k, the geometrical transformation comprising:
-rotating an angle equal to the heading reset parameter θ about an axis of a predetermined coordinate system (here the vertical axis), and
A vector equal to the position resetting parameter delta translates in a direction orthogonal to the axis.
Thus, the cost function is equal to, for exampleWherein:
- { u k}k is the set of locations evaluated at the determined time;
- { v k}k is the set of positions estimated at the determined time instant;
- { t k}k is a set of determined instants;
-N is the number of pairs of positions u (t k)、v(tk) included in the buffer memory 49;
- θ is a heading reset parameter;
R (θ) is a rotation matrix representing the direction of modification by application of a heading reset parameter, and
Delta is a location reset parameter.
Therefore, the second candidate value θ 2 is equal to
Wherein:
-u 1(tk) is a first position coordinate of the estimated position of the dead-reckoning navigation system 22 along a first axis of a predetermined fixed coordinate system at a determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest time
An average of the first position coordinates;
-u 2(tk) is the second position coordinates of the estimated position of the dead-reckoning navigation system 22 along the second axis of the predetermined fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest time
An average of the second position coordinates;
V 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of any fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest time
An average of the first position coordinates;
-v 2(tk) is the second position coordinate of the estimated position of the dead-reckoning navigation system 22 along the second axis of any fixed coordinate system at the determined time t k;
- It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest time
Average value of the second position coordinates on the first position coordinate, and
N is the number of location pairs u (t k)、v(tk) included in the buffer memory 49.
As a variant (not shown), the cost function comprises summingFor example, based on the likelihood of the term (typically the term associated with a higher variance will be given a lower weight) or the geometric distance between different terms (typically terms geometrically close to each other will be given a lower weight). As a variant, the geometric transformation is applied to the estimated position v k}k instead of the estimated position u k}k, and then the summed term is written as ||u k-R(θ)vk-Δ‖2. Still as a variant, the geometric transformation further comprises:
Track smoothing parameterized by a parameter b corrected for track angle variation bias, then writing the summed term as iiv k-R(θ+b×tk)uk-Δ‖2;
And/or
Parity, parameterized by a scaling factor h, then writing the summed term as iiv k-h×(R(θ)uk +
Δ)‖2。
This sub-step 134 is followed by a sub-step 136 of evaluating a second precision value σ θ2 associated with said second candidate value θ 2. For example, the second accuracy value σ θ2 is a function of the uncertainty σ v、σu at the estimated position { v k}k and the estimated position { u k}k. It is generally composed of the standard deviation of the second candidate value θ 2 and is given by the following formula:
wherein:
- { u k}k is the set of positions evaluated at the determined moment,
- { V k}k is the set of positions estimated at the determined time instant,
- { T k}k is a set of determined instants,
-Is the covariance of the random error affecting each coordinate of the position assessed by the relative positioning system 24,
-Is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22,
U 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of the predetermined fixed coordinate system at the determined time t k,
U 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of the predetermined fixed coordinate system at the determined time t k,
V 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of any fixed coordinate system at the determined time t k,
V 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of any fixed coordinate system at the determined time t k,
-It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest timeAn average value of the first position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest timeAn average value of the second position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest timeAn average value of the first position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined times except the oldest timeAverage value of the second position coordinates, and
N is the number of location pairs u (t k)、v(tk) included in the buffer memory 49.
As a variant, the second precision value σ θ2 is a function of the average deviation observed between the set of evaluation positions { u k}k and the set of relevant evaluation positions { v k}k corrected by means of the heading reset parameter θ having the second candidate value θ 2. For example, it is given by the following formula:
wherein:
N is the number of pairs of positions u (t k)、v(tk) included in the buffer memory 49,
- { U k}k is the set of locations evaluated at the determined time;
- { v k}k is the set of positions estimated at the determined time instant;
- is when the dead reckoning navigation system 22 is at all determined times except the oldest time The average value of the estimated positions on the table,
-Is when the dead reckoning navigation system 22 is at all determined times except the oldest timeAn average value of the estimated positions on the table,
- Θ 2 is a heading reset parameter that imparts a second candidate value θ 2, an
-R (θ 2) is a rotation matrix representing the direction modified by applying the heading reset parameter.
As a variant, the first precision value σ θ2 is a combination of a function of the uncertainty σ v、σu on the estimated positions { v k}k and { u k}k, and a function of the average deviation observed between the set of estimated positions { u k}k and the set of relevant estimated positions { v k}k corrected by means of the heading reset parameter θ having the first candidate value θ 2.
Substeps 132 and 136 are followed by substep 140 of comparing the first precision value σ θ1 with the second precision value σ θ2.
If the first precision value σ θ1 reflects a better precision than the second value σ θ2, i.e. here if σ θ1<σθ2, step 140 is followed by step 142 of selecting the first candidate value θ 1 as the selected candidate value.
On the other hand, if the precision value reflecting the best precision is constituted by the second precision value σ θ2, i.e. here if σ θ1>σθ2, step 140 is followed by step 144 of deleting the oldest point of the buffer memory 49, i.e. the position pair u associated with the oldest determination instant t 1 (t 1)、v(t1). Then the rest is determinedRenumbered asAnd steps 130 to 140 are repeated.
This makes it possible to maximize the accuracy of the reset parameter θ.
Sub-step 142 is optionally followed by a set of sub-steps 150 to 154, intended to verify the new reset parameter θ in the residual calculation.
Sub-step 142 is followed by sub-step 150 of calculating the expected reset residual r exp. The reset residuals are intended to reflect an expected average deviation between the set of estimated positions { u k}k and the set of related estimated positions { v k}k corrected by means of the heading reset parameter θ. It is given by the following formula:
wherein:
N is the number of pairs of positions u (t k)、v(tk) included in the buffer memory 49,
-Is the covariance of the random error affecting each coordinate of the position assessed by the relative positioning system 24,
-Is the covariance of the random error affecting each coordinate of the position estimated by the dead reckoning navigation system 22,
-Is the covariance of the reset parameter, θ, which is equal to the square of the standard deviation, σ θ1, of the selected candidate value, θ 1, as described above,
U 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of the predetermined fixed coordinate system at the determined time t k,
U 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of the predetermined fixed coordinate system at the determined time t k,
V 1(tk) is the first position coordinate of the estimated position of the dead reckoning navigation system 22 along the first axis of any fixed coordinate system at the determined time t k,
V 2(tk) is the second position coordinate of the estimated position of the dead reckoning navigation system 22 along the second axis of any fixed coordinate system at the determined time t k,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average value of the first position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average value of the second position coordinates on the table,
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAverage value of the first position coordinates, and
-It is the estimated position of the dead reckoning navigation system 22 at all determined timesAn average of the second position coordinates.
Sub-step 150 is followed by sub-step 152 of calculating the observed reset residual r obs. The reset residuals are intended to reflect the average deviation observed between the set of estimated positions { u k}k and the set of related estimated positions { v k}k corrected by means of the heading reset parameter θ given the selected candidate value θ 1. It is given by the following formula:
wherein:
N is the number of pairs of positions u (t k)、v(tk) included in the buffer memory 49,
- { U k}k is the set of locations evaluated at the determined time;
- { v k}k is the set of positions estimated at the determined time instant;
- is a set of dead reckoning navigation systems 22 at a determined time The average value of the estimated positions on the table,
-Is a set of dead reckoning navigation systems 22 at a determined timeAn average value of the estimated positions on the table,
- Θ is a heading reset parameter, and
-R (θ) is a rotation matrix representing the direction modified by applying the heading reset parameter.
Sub-step 152 is followed by sub-step 154 of comparing the observed reset residual r obs with the expected reset residual r exp increased by a predetermined threshold δ.
If the observed reset residual r obs is strictly greater than the sum of the expected reset residual r exp and the threshold δ, i.e. if the inequality r obs>rexp +δ is satisfied, then sub-step 154 is followed by sub-step 156 of rejecting the selected candidate value. Then, the reset parameter θ maintains its previous value.
If the observed reset residual r obs is less than or equal to the sum of the expected reset residual r exp and the threshold r exp, i.e. if the inequality r obs≤rexp +δ is satisfied, sub-step 154 is followed by sub-step 158 of comparing the precision value σ θn associated with the selected candidate value with the precision value σ θo associated with the current value of the reset parameter θ. It should be noted that, in view of the candidate selection algorithm, the precision value σ θn associated with the selected candidate is equal to the first precision value σ θ1 described above.
More specifically, sub-step 158 includes comparing the precision value σ θn associated with the selected candidate value to the precision value σ θo associated with the current value of the reset parameter θ that increases by a time drift value proportional to the time elapsed between the determination of the selected candidate value and the determination of the current value of the heading reset parameter θ. The time drift value is typically equal to (t n-to) x b, where:
T n is the time representing the determination time t k}k considered for determining the selected candidate value,
-T o is the time representing the determination time { t k}k considered for determining the current value of the heading reset parameter θ, and
B is a predefined constant representing a typical deviation value of gyroscope 40.
Each time instant t o、tn consists, for example, of an average value of the determination times { t k}k considered for determining the selected candidate value and for determining the current value of the heading reset parameter θ, respectively. As a variant, each instant t o、tn is constituted, for example, by the most recently determined instant t k considered for determining the selected candidate value and for determining the current value of the heading reset parameter θ, respectively.
In the case where substep 158 is performed for the first time after the start-up of the dead reckoning navigation system 22, the precision value σ θo associated with the current value of the reset parameter θ is preferably infinity.
Substep 158 is followed by substep 160 of determining a future value of the reset parameter θ based on the result of comparison 158. The future value is typically a function of the candidate value and the current value.
For example, if the precision value σ θn associated with the selected candidate value is greater than or equal to the precision value σ θo associated with the current value, the current value is increased by a time drift value, i.e., if the inequality σ θn≥σθo+(tn-to) x b is satisfied, the future value is equal to the current value, and on the other hand, if the precision value σ θn associated with the selected candidate value is strictly less than the precision value σ θo associated with the current value, the current value is increased by a time drift value, i.e., if the inequality σ θn<σθo+(tn-to) x b is satisfied, the future value is equal to the selected candidate value.
As a variant, the future value is equal to the combination of the selected candidate value and the current value, typically by applying a kalman filter or bayesian fusion, depending on the ratio between the precision value σ θn associated with the selected candidate value and the precision value σ θo associated with the current value increased by the time drift value. For example, the future value is equal to Wherein:
-theta n is a selected candidate value,
Σ θn is the precision value associated with the selected candidate,
- Θ o is the current value of the heading reset parameter θ, and
- Σ θo is the precision value associated with the current value.
This substep 160 ends the step 124 of inferring the heading reset parameter θ.
Returning to FIG. 5, step 124 is followed by step 126 of adjusting the estimated heading. During this step 126, the dead reckoning navigation system 22 adjusts the estimated heading by applying the heading reset parameter θ:
this step 126 ends the heading reset step 107.
Returning to fig. 4, the position reset step 106 and heading reset step 107 are followed by a step 109 of the dead reckoning navigation system 22 calculating the position of the pedestrian 12. During this step 109, the dead reckoning navigation system 22 applies heading and position reset parameters to determine the position of the pedestrian 12 in a predetermined coordinate system. The position is determined by the following formula: wherein:
- is the position of the pedestrian 12 in a predetermined coordinate system calculated by the dead reckoning navigation system 22,
V (t) is the position of the pedestrian 12 in any coordinate system estimated by the dead reckoning navigation system 22,
Θ is a heading reset parameter,
-R (θ) T is a rotation matrix representing the modification of direction by applying the inverse of the heading reset parameter, and
Delta is a location reset parameter.
The method 100 then loops back to step 109 to allow for the calculated position to be locatedContinuous updating is performed.
At the same time, the method 100 returns to step 104 to allow continuous updating of the heading reset parameter θ and the position reset parameter Δ each time the pedestrian 12 passes near the beacon 54.
Thanks to the above described exemplary embodiments, the movements of persons within a building can be accurately tracked in a simple and economical manner. This is indeed achieved thanks to the particularly lightweight infrastructure 18 that only needs to be deployed and the particularly simple localization boxes 16 that only need to be equipped for the person being tracked. The motion sensors 30 equipped with these cartridges 16 need not be very accurate because the dead reckoning navigation system can be reset periodically each time a person passes near the infrastructure 18.
In particular, the use of UWB technology for the relative positioning system 24 is particularly advantageous, since it allows to obtain a very accurate reset in a small range of movements due to the low error level of UWB positioning. Thus, it can greatly reduce infrastructure requirements. It is also completely transparent to the pedestrian 12 and the pedestrian 12 does not have to perform any special task to ensure the resetting of its localiser box 16.
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| FRFR2207063 | 2022-07-08 | ||
| PCT/FR2023/051071 WO2024009048A1 (en) | 2022-07-08 | 2023-07-10 | Method for correcting an attitude provided by a dead reckoning navigation system by means of a relative positioning system |
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| US9816818B2 (en) * | 2010-12-03 | 2017-11-14 | Qualcomm Incorporated | Inertial sensor aided heading and positioning for GNSS vehicle navigation |
| FR2977313B1 (en) | 2011-06-28 | 2013-08-09 | Centre Nat Etd Spatiales | SPACE ENGINE WITH SPEED VECTOR ESTIMATING DEVICE AND CORRESPONDING ESTIMATION METHOD |
| US10088318B2 (en) * | 2015-08-27 | 2018-10-02 | Qualcomm Incorporated | Cradle rotation insensitive inertial navigation |
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| US10197400B2 (en) * | 2016-02-25 | 2019-02-05 | Sharp Laboratories Of America, Inc. | Calibration methods and systems for an autonomous navigation vehicle |
| FR3069634B1 (en) | 2017-07-28 | 2021-06-11 | Sysnav | METHOD AND DEVICE FOR CHARACTERIZING A DETERMINED HEADING FROM MEASUREMENT OF THE MAGNETIC FIELD |
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2023
- 2023-07-10 KR KR1020257003051A patent/KR20250033245A/en active Pending
- 2023-07-10 WO PCT/FR2023/051071 patent/WO2024009048A1/en active Application Filing
- 2023-07-10 CN CN202380052599.0A patent/CN119546924A/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| FR3137764B1 (en) | 2024-07-12 |
| FR3137764A1 (en) | 2024-01-12 |
| WO2024009048A1 (en) | 2024-01-11 |
| KR20250033245A (en) | 2025-03-07 |
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