Summary of the invention
The localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, comprising:
Obtain indoor map data;
Obtain the indoor visible light communication location data of user equipment;
Obtain the indoor inertial navigation location data of user equipment;
In conjunction with indoor visible light communication location data, indoor inertial navigation location data and indoor map data, to user equipment
The indoor location at place is combined positioning,
Wherein, it is seen that optic communication location data and/or indoor inertial navigation location data be by Extended Kalman filter and/or
Location data handled by neural network deep learning, for being combined positioning.
The localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, visible light communication position number
According to including at least one of following: measured value, the visible light signal for the visible light signal intensity that user equipment receives reach
The estimated value of the distance between measured value, user equipment and the VISIBLE LIGHT EMISSION equipment of the angle of user equipment, first user's row
Mark estimated value, indoor inertial navigation location data includes at least one of following: the measured value of magnetometer, gyroscope measured value,
The measured value of accelerometer, second user trace estimated value, user's direction of travel estimated value, user's step-size estimation value.
The localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, wherein the body based on user
At least one of height, weight, state of ground, user's acceleration, user's stride frequency, by neural network to user's step value into
Row deep learning, with establish at least one of the height of user, weight, state of ground, user's acceleration, user's stride frequency with
The corresponding relationship of family step value, to obtain accurate user's step-size estimation value.
The localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, Extended Kalman filter are
Indirect method Extended Kalman filter.
The localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, further includes:
The initial position of user equipment is obtained, is calculated with carrying out the accumulation of second user trace estimated value.
The positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, comprising:
Map datum obtains module, for obtaining indoor map data;
Visible light communication location data obtains module, for obtaining the indoor visible light communication location data of user equipment;
Inertial navigation location data obtains module, for obtaining the indoor inertial navigation location data of user equipment;
Integrated positioning module, in conjunction with indoor visible light communication location data, indoor inertial navigation location data and indoor ground
Diagram data is combined positioning to the indoor location where user equipment;
Extended Kalman filter module, for being carried out to visible light communication location data and/or indoor inertial navigation location data
Extended Kalman filter, to obtain location data by Extended Kalman filter, for being combined positioning;And/or
Neural network module, for carrying out depth to visible light communication location data and/or indoor inertial navigation location data
It practises, to obtain location data by the processing of neural network deep learning, for being combined positioning.
The positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, visible light communication position number
According to including at least one of following: measured value, the visible light signal for the visible light signal intensity that user equipment receives reach
The estimated value of the distance between measured value, user equipment and the VISIBLE LIGHT EMISSION equipment of the angle of user equipment, first user's row
Mark estimated value, indoor inertial navigation location data includes at least one of following: the measured value of magnetometer, gyroscope measured value,
The measured value of accelerometer, second user trace estimated value, user's direction of travel estimated value, user's step-size estimation value.
The positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, neural network module are also used
In:
At least one of height, weight, state of ground, user's acceleration, user's stride frequency based on user, to pass through mind
Deep learning is carried out to user's step value through network, to establish the height, weight, state of ground, user's acceleration, user of user
The corresponding relationship of at least one of cadence and user's step value, to obtain accurate user's step-size estimation value.
The positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, Extended Kalman filter are
Indirect method Extended Kalman filter.
The positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, further includes:
Initial position obtains module, for obtaining the initial position of user equipment, to carry out second user trace estimated value
Accumulation calculate.
Above-mentioned technical proposal according to the present invention, combines visible light-seeking and the respective technology of inertial sensor positioning is excellent
Gesture improves the precision that inertial sensor positions continuous long-time indoor positioning.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiments of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
Member's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.It needs
It is noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can mutual any combination.
In order to preferably meet people for the use demand of indoor positioning, the present invention is based on will be seen that optic communication
(Visual Light Communication, VLC) positioning is merged with inertial sensor positioning (that is, inertial navigation positioning), is used
In the inventive concept of indoor positioning, following technical scheme is proposed.
Fig. 1 schematically illustrates the localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention
Schematic flow diagram.
As shown in the solid box of Fig. 1, the localization method of the positioning of combination visible light communication and inertial navigation positioning according to the present invention,
Include:
Step S102: indoor map data are obtained;
Step S104: the indoor visible light communication location data of user equipment is obtained;
Step S106: the indoor inertial navigation location data of user equipment is obtained;
Step S108: right in conjunction with indoor visible light communication location data, indoor inertial navigation location data and indoor map data
Indoor location where user equipment is combined positioning,
Wherein, it is seen that optic communication location data and/or indoor inertial navigation location data are by spreading kalman (Kalman)
Filtering and/or location data handled by neural network deep learning, for being combined positioning.
Visible light communication location data derives from visible light communication reception device (for example, may be mounted on user equipment)
Illumination detected, from visible light communication emitter (for example, a kind of new LED illumination device) and signal of communication.
Different LED illumination devices loads id information relevant to its position, when user equipment receives some position
When id information, i.e., it is believed that the user equipment is located at its corresponding LED illumination device.I.e., it is possible to preset during installation
Location information (corresponding to above-mentioned id information) built in good LED illumination device can be position when LED illumination device enables
Information is loaded on issued visible light signal, is decoded by user equipment, so that it may the coordinate for obtaining LED illumination device, into
And the coordinate of user equipment is resolved according to the coordinate of LED illumination device.For example, user equipment can map received data
Onto indoor (high-precision) map, to realize the positioning function based on indoor map, positioning accuracy is adjacent illumination light source
The 1/2 of distance.
The user that inertial navigation location technology is measured using the gyroscope, accelerometer, magnetometer etc. installed on user equipment
The angular velocity information of equipment space and than force information, by resolving ordinary differential system, obtains user equipment and sits in navigation
Position, speed, posture and temporal information in mark system.
What inertial navigation location technology can be realized user equipment track self calculates, provides consecutive tracking (navigation) scheme,
There is very high positioning (navigation) precision in short time.Inertial navigation location technology is not limited by any external environment, in various rings
Under border all effectively, other localization methods compared with the prior art have the advantage that
1, deployment O&M is few, at low cost.Compared with the schemes such as UWB, RFID, inertial navigation independent of any external signal,
Not to external radiation signal, do not influenced by outside electromagnetic interference, thus dispose it is extremely low, once deployment success is subsequent without complicated
Base station and terminal O&M can greatly reduce positioning system cost by reducing to dispose and subsequent O&M is greatly decreased.
2, easy-to-use, it is low to demanding terminal.Compared with other location technologies, it is not necessarily to special hardware positioning terminal, it can be simultaneous
Hold all kinds of intelligent terminals such as mobile phone, it, can be direct it is not necessary that positioning terminal is provided and recycled to everyone in the big scene of flow of the people
Positioning service is provided in the form of app etc., it is easy to use.
3, precision is high, is not influenced by complex environment.For all technologies positioned using wireless signal, all exist multiple
The problem of signal blocks and interference bring position error in heterocycle border increase.And inertial navigation is independent of outside positioning letter
Number, thus same positioning accuracy is persistently maintained in complex environment.
However, but there is constant error and/or random drift in inertial navigation positioning, when individually being positioned for a long time,
Biggish position error will be accumulated, to substantially reduce positioning accuracy.
In view of visible light communication localization method realizes that simple, broad covered area, there is no accumulation position errors.Therefore, may be used
Will be seen that optic communication location data is combined with inertial navigation location data.For example, visible light communication location data can be based on
It rectifies a deviation to inertial navigation positioning measurement data, so that the constant error and/or random drift of inertial navigation positioning measurement data are eliminated, from
And indoor position accuracy is improved, with good application prospect.
Since visible light communication positioning depends on the received light signal of user equipment, and light signal is not to deposit at the moment
So about several meters or so of the result (depending on lamps and lanterns layout density) of visible light communication positioning will be updated once.And for
For the reckoning mode of inertial navigation positioning, the user of Portable device, which often makes a move, will obtain a new position, so used
Property positioning result to export with result that visible light communication position be not synchronous.
In order to solve this problem, for example, above-mentioned technical proposal according to the present invention can use Extended Kalman filter
Mode the result of visible light positioning result and inertia measurement is merged, while being also convenient for making up inertial navigation positioning institute for a long time
The accumulated error of generation.
Kalman Filter Technology has important meaning to visible light/inertial navigation integrated navigation development.According to Kalman filtering
State (i.e. it is desired to signal or expected data) estimated by device (including filtering) is different, and Kalman filtering is in integrated navigation
Using being divided into direct method and indirect method.Direct method estimation navigational parameter (including above-mentioned visible light communication location data, interior are used to
Lead location data) itself, indirect method estimates the error of navigational parameter.
The input signal of direct method (extension) Kalman filter is that the specific force of inertial navigation system measurement (corresponds to above-mentioned interior
Inertial navigation location data) or the positional parameter (correspond to above-mentioned visible light communication location data) that calculates of visible light positioning system, warp
Filtering parameter calculating and filtering operation are crossed, the optimal estimation of each autocorrelative positional parameter is exported.Estimated using direct method
When, state equation and measurement equation are likely to be nonlinear, since the positional parameter of movable body is generally not a small amount of, equation line
Propertyization can bring large error, and the calculating of filter parameter need to spend more time, this makes the refresh cycle of positional parameter
It can not be too fast, it is difficult to meet the requirement that dynamic carrier (that is, user equipment) updates positional parameter.Therefore, in the prior art
Positioning System in, it is less use direct method (extension) Kalman filtering.
The input signal of indirect method (extension) Kalman filter is the difference or visible light positional parameter of inertial navigation system parameter
Difference, by filtering parameter calculate and filtering operation, export the optimal estimation of each auto-correlated error.Estimated using indirect method
Timing, so-called " system " are actually exactly " combination " of the various errors of positioning system, and system mode is a small amount of, equation linearisation
The error brought into is smaller.Filter calculate when, the calculation process of original system is not involved in and independence, for original system, in addition to connecing
Outside by the correction of error estimator, so that keeping the independence of its work.This enables indirect method to give full play to the spy of each system
Point, thus be widely adopted.The state of indirect method estimation is all error state, i.e., the state vector in filtering equations is positioning ginseng
The set of number error state and other error states.
Optionally, it is seen that optic communication location data includes at least one of following: the visible light that user equipment receives
Measured value, user equipment and the VISIBLE LIGHT EMISSION for the angle that measured value, the visible light signal of signal strength reach user equipment are set
The distance between standby estimated value, first user's trace estimated value, indoor inertial navigation location data includes at least one of following:
The measured value of magnetometer, the measured value of gyroscope, the measured value of accelerometer, second user trace estimated value, user traveling side
To estimated value, user's step-size estimation value.
For example, indoor inertial navigation location data may include following data: the acceleration of three-dimensional (corresponds to above-mentioned acceleration
Spend the measured value of meter);The angular speed (measured value corresponding to above-mentioned gyroscope) of three-dimensional;(relative to magnetic north direction) three
Tie up the electromagnetic field magnetic azimuth (measured value corresponding to above-mentioned magnetometer) in direction;Longitude, latitude, height, speed and route are (right
It should be in above-mentioned second user trace estimated value).
For example, being used for according to inertial parameter (corresponding to the measured value of above-mentioned magnetometer, the measured value of gyroscope, acceleration
The measured value of meter) the resolving model of the position (correspond to above-mentioned second user trace estimated value) of user equipment that determines include with
Lower two kinds: continuous integral model and reckoning model.
Optionally, at least one of the height based on user, weight, state of ground, user's acceleration, user's stride frequency,
To carry out deep learning to user's step value by neural network, to establish the height, weight, state of ground, Yong Hujia of user
The corresponding relationship of at least one of speed, user's stride frequency and user's step value, to obtain accurate user's step-size estimation value.
For example, the neural network by deep learning after training, can according to the practical height of actual user, weight,
Actual ground situation, actual user's acceleration, actual user's cadence or its estimated value, the automatic accurate estimation for exporting user's step-length
Value, to further improve the precision of indoor positioning.
Optionally, Extended Kalman filter is indirect method Extended Kalman filter.
Optionally, as shown in the dotted line frame of Fig. 1, the positioning of combination visible light communication and inertial navigation positioning according to the present invention are determined
Position method, further includes:
Step S110: obtaining the initial position of user equipment, is calculated with carrying out the accumulation of second user trace estimated value.
For example, above-mentioned indoor map data (including accurately diagram data) can store in server end, it can also be following
Load is stored on the user equipmenies such as mobile phone, plate or computer.
For example, above-mentioned localization method can execute on the user equipmenies such as mobile phone, plate or computer, it can also be in server
End executes, or after server end execution, to user equipment restoring to normal position result.
Fig. 2 schematically illustrates the positioning device of the positioning of combination visible light communication and inertial navigation positioning according to the present invention
Schematic block diagram.
As shown in Fig. 2, the positioning device 200 of the positioning of combination visible light communication and inertial navigation positioning according to the present invention, comprising:
Map datum obtains module 201, for obtaining indoor map data;
Visible light communication location data obtains module 203, and the indoor visible light communication for obtaining user equipment positions number
According to;
Inertial navigation location data obtains module 205, for obtaining the indoor inertial navigation location data of user equipment;
Integrated positioning module 207, in conjunction with indoor visible light communication location data, indoor inertial navigation location data and interior
Map datum is combined positioning to the indoor location where user equipment;
Extended Kalman filter module 209, for visible light communication location data and/or indoor inertial navigation location data into
Row Extended Kalman filter, to obtain location data by Extended Kalman filter, for being combined positioning;And/or
Neural network module 211, for carrying out depth to visible light communication location data and/or indoor inertial navigation location data
Study, to obtain location data by the processing of neural network deep learning, for being combined positioning.
Optionally, it is seen that optic communication location data includes at least one of following: the visible light that user equipment receives
Measured value, user equipment and the VISIBLE LIGHT EMISSION for the angle that measured value, the visible light signal of signal strength reach user equipment are set
The distance between standby estimated value, first user's trace estimated value, indoor inertial navigation location data includes at least one of following:
The measured value of magnetometer, the measured value of gyroscope, the measured value of accelerometer, second user trace estimated value, user traveling side
To estimated value, user's step-size estimation value.
Optionally, neural network module 211 is also used to:
At least one of height, weight, state of ground, user's acceleration, user's stride frequency based on user, to pass through mind
Deep learning is carried out to user's step value through network, to establish the height, weight, state of ground, user's acceleration, user of user
The corresponding relationship of at least one of cadence and user's step value, to obtain accurate user's step-size estimation value.
Optionally, Extended Kalman filter is indirect method Extended Kalman filter.
Optionally, as shown in the dotted line frame of Fig. 2, the positioning of combination visible light communication and inertial navigation positioning according to the present invention are determined
Position device 200, further includes:
Initial position obtains module 213, for obtaining the initial position of user equipment, to carry out second user trace estimation
The accumulation of value calculates.
In order to make those skilled in the art be more clearly understood that above-mentioned technical proposal according to the present invention, below in conjunction with tool
Body embodiment is described.
Fig. 3, which is schematically illustrated, may be implemented determining for the positioning of combination visible light communication and inertial navigation positioning according to the present invention
The schematic diagram of one embodiment of position technical solution.
As shown in figure 3, the embodiment includes that " inertial sensor positioning " module (corresponds to above-mentioned inertial navigation location data to obtain
Module 205), " visible light-seeking " module (correspond to above-mentioned visible light communication location data obtain module 203) and " karr
Graceful filtering " module (corresponds to above-mentioned Extended Kalman filter module 209).
For example, the operation that " inertial sensor positioning " module can execute includes:
1, it obtains sensing data and (corresponds to above-mentioned indoor inertial navigation location data, measured value, gyroscope including magnetometer
Measured value, the measured value of accelerometer etc.).
2, data prediction.
3, track (that is, above-mentioned user's trace) calculates.
4, gait detects.
5, step-size estimation.
6, course (that is, above-mentioned user's direction of travel) is estimated.
7, high-precision map match.
8, the detection data for coming from " visible light-seeking " module is received, (calibration) is adjusted to the detection data of itself.
For example, the operation that " visible light-seeking " module can execute includes:
1, location information compiles (solution) code.
2, lamplight modulation (demodulation).
3, RSS (received signal strength)/AOA (angle of arrival) detection algorithm.
4, smooth trajectory and prediction.
5, data be will test and be sent to " inertial sensor positioning " module.
For example, " Kalman filtering " module can to from " inertial sensor positioning " module detection data and/or
The operation executed from the detection data of " visible light-seeking " module includes:
1, system mode vector is predicted.
2, systematic observation vector forecasting.
3, state vector transfer matrix is calculated.
4, gain matrix is calculated.
5, state vector optimal estimation.
6, state vector variance matrix updates.
Fig. 4, which is schematically illustrated, may be implemented determining for the positioning of combination visible light communication and inertial navigation positioning according to the present invention
The schematic diagram of another embodiment of position technical solution.
As shown in figure 4, the embodiment may include following operation:
1, " high-precision cartographic information " (corresponding to the above-mentioned steps S102 for combining Fig. 1 description) is obtained.
2, obtain sensing data (correspond to above-mentioned indoor inertial navigation location data, including " accelerometer " shown in Fig. 4,
" gyroscope ", " direction sensor " --- such as the measured value of magnetometer).
3, correspond to above-mentioned steps S106, based on " dynamic initialization " position and, based on sensing data (for example, making
The PDR algorithm performed by " PDR processing module ") the gait detection that is carried out, step-size estimation, user (pedestrian) state sentence
It is disconnected, carry out indoor inertial navigation positioning.
For example, as shown in figure 4, gait detection, step-size estimation, user can be carried out based on the measured value of " accelerometer "
The judgement of (pedestrian) state.
For example, as shown in figure 4, the measured value for being also based on " gyroscope " carries out step-length, direction angle increment, deflection
Detection or estimation.
For example, the detection of " visible light signal " " synchronous adjustment " gait, step-size estimation, user (pedestrian) state can be based on
The result of judgement.
4, correspond to above-mentioned steps S104, " VLC processing module " can be used and (correspond to above-mentioned visible light communication and position number
According to acquisition module 203), " visible light signal " Lai Jinhang visible light communication positioning based on shown in Fig. 4.
5, correspond to above-mentioned steps S108, can the location data (for example, position data) based on " VLC processing module " come
The location data of " dynamic initialization " (that is, adaptive adjustment, adaptive calibration) " PDR processing module ", to improve " at PDR
The positioning accuracy of reason module ".
6, by " EKF (extended Kalman filter, Extended Kalman Filter) " module to " PDR handles mould
The location data progress EKF filtering of block ", " VLC processing module " realizes high-precision so that the effect for positioning fusion is more preferable
Positioning.
For example, " EKF " module may include EKF state vector update module and EKF observation vector update module.
It is similar with Kalman Filtering for Discrete, for example, the observational equation and state equation in Extended Kalman filter model can
Is defined as:
xk=fk(xk-1)+wk
zk=hk(xk)+vk
Wherein, fk(xk-1) indicate nonlinear transfer relationship of the state vector between k moment and previous moment, hk(xk) table
Show the non-linear relation of k moment observation vector and state vector, wkFor the state vector noise matrix that n × 1 is tieed up, vkFor m × 1
Observation vector noise matrix.
It may comprise steps of for example, Extended Kalman filter solution to model calculates method:
1, the predicted value of computing system state vector
2, the predicted value of computing system observation vector
3, state-transition matrix is calculatedWith measurement matrix Hk。
4, the variance prediction matrix of state vector is calculated
5, gain matrix K is calculatedk。
6, the optimal estimation value of current state vector is obtained
7, the variance matrix of current state vector is updated
That is, embodiment shown in Fig. 4, it can be (corresponding using VLC-PDR fusion and positioning method based on the filtering algorithm of EKF
Accurate indoor positioning is realized in above-mentioned steps S108).
For example, embodiment shown in Fig. 4 may include step in detail below:
1, filtering initial state vector is set using VLC positioning (that is, above-mentioned visible light communication positions) result.
2, by VLC position on the basis of dynamically correct PDR positioning (that is, above-mentioned interior inertial navigation positioning).
3, travel condition (gait detection etc.) is judged using acceleration information, according to high-precision indoor map information combination side
Pedestrian course is obtained to sensor and gyroscope.
4, when pedestrian (that is, holding equipment user) walks, VLC processing module is notified to carry out by " synchronous adjustment " module
Target positioning calculation starts the iterative calculation of measurement updaue and state update.
Since visible light-seeking depends on the received light signal of mobile phone, and light signal is not to exist at the moment, so can
About several meters or so of the result of light-exposed positioning (depending on lamps and lanterns layout density) will be updated primary.And for PDR positioning, row
People position is real-time update, so the output of two kinds of positioning results is nonsynchronous.Therefore, embodiment shown in Fig. 4 uses
The mode of EKF merges the result of visible light positioning result and inertia measurement, while being also convenient for making up inertial navigation for a long time calmly
Accumulated error caused by position.
Above-mentioned technical proposal according to the present invention, has the advantage that
1, it preferably combines visible light-seeking and inertial sensor positions respective technical advantage, it is fixed to realize visible light
The correction (for example, periodically correction, adaptive dynamic correcting etc.) that position combining cartographic information positions inertial sensor, effectively mentions
High inertial sensor positions the precision of continuous long-time indoor positioning.
2, at low cost, few without wireless communication signals radiation (that is, electromagnetic radiation), strong security, add-on module.
3, it is high to have both illumination/communication/positioning function, bandwidth for visible light-seeking.
Descriptions above can combine implementation individually or in various ways, and these variants all exist
Within protection scope of the present invention.
It will appreciated by the skilled person that whole or certain steps, system, dress in method disclosed hereinabove
Functional module/unit in setting may be implemented as software, firmware, hardware and its combination appropriate.In hardware embodiment,
Division between the functional module/unit referred in the above description not necessarily corresponds to the division of physical assemblies;For example, one
Physical assemblies can have multiple functions or a function or step and can be executed by several physical assemblies cooperations.Certain groups
Part or all components may be implemented as by processor, such as the software that digital signal processor or microprocessor execute, or by
It is embodied as hardware, or is implemented as integrated circuit, such as specific integrated circuit.Such software can be distributed in computer-readable
On medium, computer-readable medium may include computer storage medium (or non-transitory medium) and communication media (or temporarily
Property medium).As known to a person of ordinary skill in the art, term computer storage medium is included in for storing information (such as
Computer readable instructions, data structure, program module or other data) any method or technique in the volatibility implemented and non-
Volatibility, removable and nonremovable medium.Computer storage medium include but is not limited to RAM, ROM, EEPROM, flash memory or its
His memory technology, CD-ROM, digital versatile disc (DVD) or other optical disc storages, magnetic holder, tape, disk storage or other
Magnetic memory apparatus or any other medium that can be used for storing desired information and can be accessed by a computer.This
Outside, known to a person of ordinary skill in the art to be, communication media generally comprises computer readable instructions, data structure, program mould
Other data in the modulated data signal of block or such as carrier wave or other transmission mechanisms etc, and may include any information
Delivery media.
Finally, it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations.Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that: it still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features;
And these are modified or replaceed, the spirit of the technical solution for various embodiments of the present invention that it does not separate the essence of the corresponding technical solution
And range.