UWB indoor positioning method based on RTK difference thought

Abstract

The invention discloses a UWB indoor positioning method based on an RTK difference thought, and relates to the technical field of indoor positioning. Comprising a base station, reference stations and a mobile station, and specifically comprises the following steps that 1, UWB signals are sent through the base station, a plurality of reference stations with known accurate coordinates are deployed indoors, the reference stations are UWB anchor points, and the positions of the reference stations are calibrated in advance through laser surveying and mapping; according to the method, the base station with the known accurate position is deployed indoors, the base station is used for calculating the error in the UWB signal propagation process, the error correction information is sent to the mobile station, and the mobile station corrects the distance measurement result of the mobile station according to the correction information, so that the precision and the stability of UWB indoor positioning are improved. The UWB indoor positioning method effectively solves the problem of positioning errors caused by factors such as multipath effect, non-line-of-sight and clock drift in UWB indoor positioning, and is suitable for various indoor scenes such as industrial storage, medical care for the aged and emergency rescue.

Description

Technical Field

[0001] The present invention relates to the field of indoor positioning technology, and in particular to a UWB indoor positioning method based on RTK differential thinking. Background Art

[0002] With the advancement of science and technology and internet information technology, people have a growing demand for indoor positioning, such as meeting friends at the mall, checking store locations, and navigating to vacancies in underground garages. UWB signals, with their high resolution and multipath robustness, hold broad application prospects in indoor positioning. However, in complex indoor environments, UWB signals are affected by multipath, non-line-of-sight (NLOS), clock drift, hardware latency, and other factors, resulting in significant positioning errors and making it difficult to meet the demand for high-precision positioning.

[0003] RTK (Real-Time Kinematic Differential Positioning) technology uses satellite signals to eliminate common errors through a differential mechanism between a base station and a rover, achieving centimeter-level positioning. While it is primarily suitable for outdoor use and cannot be directly applied indoors, its differential principle provides valuable insights and reference for UWB indoor positioning.

[0004] Therefore, the present invention proposes a UWB indoor positioning method and system based on RTK differential idea, which applies the RTK differential idea to UWB indoor positioning to improve the accuracy and stability of UWB indoor positioning. Summary of the Invention

[0005] (1) Technical problems solved

[0006] In view of the deficiencies of the prior art, the present invention provides a UWB indoor positioning method based on RTK differential thinking, which solves the problems raised in the above background technology.

[0007] (2) Technical solution

[0008] In order to achieve the above-mentioned purpose, the present invention specifically adopts the following technical solutions:

[0009] A UWB indoor positioning method based on RTK differential thinking includes a base station, a reference station, and a mobile station, and specifically includes the following steps:

[0010] Step 1: Send UWB signals through the base station and deploy multiple reference stations with known precise coordinates indoors. The reference stations are UWB anchor points, and their positions are pre-calibrated through laser mapping;

[0011] The base station is used to send UWB signals;

[0012] The reference station is deployed at a known precise location indoors to measure the distance to other anchor points and mobile stations, calculate errors and send error correction information;

[0013] Step 2: The base station measures the distance to other anchor points and the rover in real time, calculates the difference between the measured distance and the actual distance, and establishes an error model;

[0014] Step 3: The base station sends the error model to the mobile station;

[0015] The mobile station is used to receive the error correction information sent by the reference station, correct its own distance measurement result, and calculate its own position;

[0016] Step 4: The mobile station receives the error model and corrects the distance measurement results between itself and each anchor point;

[0017] Step 5: The mobile station calculates its own position based on the corrected distance using the weighted least squares method.

[0018] Furthermore, the base station includes a UWB module, a high-precision crystal oscillator, a temperature and humidity sensor, and a communication module. The UWB module is used to send and receive UWB signals and measure distance. The high-precision crystal oscillator is used to reduce clock drift errors. The temperature and humidity sensor is used to monitor environmental parameters. The communication module is used to send error correction information.

[0019] Furthermore, the mobile station includes a UWB module and a communication module, the UWB module is used to receive UWB signals and measure distances, and the communication module is used to receive error correction information sent by the reference station.

[0020] Furthermore, in step one, the deployment of the reference station meets the following conditions: the position is stable in the long term and fixed by bolts; there is as little obstruction as possible between the reference station and the mobile station, or the non-line-of-sight error can be compensated through environmental modeling; in a complex environment, the distance between the reference stations does not exceed 10 meters.

[0021] Furthermore, in step 2, the error model includes systematic error and environmental error. The systematic error includes clock drift error and hardware delay error. The environmental error includes multipath error and non-line-of-sight error. Suppose the error model for:

[0022]

[0023] in, is the systematic error, is the environmental error.

[0024] Furthermore, the clock drift error is calculated by a cross-correlation algorithm between reference stations, and the hardware delay error is pre-calibrated by a loopback test. The specific algorithm is as follows:

[0025] Systematic error The expression is:

[0026]

[0027] in, is the clock drift error, is the hardware delay error;

[0028] The clock drift error is calculated by the cross-correlation algorithm between the reference stations. Assume that the signal sequence received by the reference station A is The signal sequence received by reference station B is ,in Represents the serial number of the sampling point, and then the clock drift is analyzed by calculating the cross-correlation function of the two signal sequences. The calculation formula is:

[0029]

[0030] in, Indicates the relative displacement between signal sequences, is the total number of sampling points, by adjusting The value of , traverse all possible displacement situations, and find the corresponding value when the cross-correlation function reaches the maximum value Value, recorded as ;

[0031] Since the time deviation caused by clock drift will be reflected in the relative displacement of the signal sequence, The clock drift error between reference stations A and B can be calculated, assuming the sampling interval is , then the clock drift error It can be expressed as: ;

[0032] The hardware delay error is pre-calibrated to .

[0033] Furthermore, the multipath effect error and non-line-of-sight error are identified by signal strength and channel impulse response analysis, and the correction weights are dynamically adjusted using Kalman filter residual analysis. The specific algorithm is as follows:

[0034] Environmental error The expression is:

[0035]

[0036] in, is the peak ratio of CIR, is the scene coefficient, calibrated through experiments;

[0037] CIR peak ratio and signal strength threshold judgment:

[0038] Viewing distance: and ;

[0039] Weak multipath: and ;

[0040] Strong multipath / non-line-of-sight: or ;

[0041] in, is the peak ratio of CIR, is the attenuation of signal strength, It is the maximum attenuation of signal strength under line of sight obtained by measuring the attenuation of signal strength multiple times;

[0042] Peak Ratio The formula is:

[0043]

[0044] in, is the energy of the first peak in CIR, the direct wave energy, is the total energy of all peaks in CIR, is the number of identifiable peaks in the CIR;

[0045] Signal strength attenuation The formula is:

[0046]

[0047] in, is the reference intensity under the preset line-of-sight environment, is the UWB signal receiving strength;

[0048] The state equation and observation equation of the Kalman filter model in Kalman filter residual analysis are:

[0049]

[0050]

[0051] in, for The estimated state value at time t, for The optimal state estimate at time , is the state transition matrix, is the process noise, for The measured value at the moment, is the anchor point coordinate, is the observation noise;

[0052] residual The formula is:

[0053]

[0054] in, is the observation value predicted based on the state at the previous moment;

[0055] Covariance matrix of the residuals for:

[0056]

[0057] in, is the observation matrix, is the predicted state covariance, is the observation noise covariance;

[0058] Correction weight Dynamic adjustment formula:

[0059]

[0060] in, is the initial weight, based on the CIR peak ratio set up: , that is, in line-of-sight environment , strong multipath , is the adjustment coefficient, is the trace of the residual covariance matrix.

[0061] Furthermore, in the step 3, the reference station encapsulates the error model into a differential frame and sends it to the mobile station via UWB, wherein the differential frame includes a timestamp, a reference station ID, a correction parameter and a check bit.

[0062] Furthermore, in step 4, the formula used by the mobile station to correct the distance measurement result is:

[0063]

[0064] in, is the corrected distance, To measure distance, The amount of error calculated for the reference station.

[0065] Furthermore, in step 5, the mobile station calculates its own position using the weighted least squares method based on the corrected distance, and the objective function is:

[0066]

[0067] in, is the number of anchor points involved in positioning, For the The coordinates of the mobile station are solved by this objective function as (x, y).

[0068] (3) Beneficial effects

[0069] Compared with the existing technology, the present invention provides a UWB indoor positioning method based on RTK differential thinking, which has the following beneficial effects:

[0070] The present invention introduces the differential concept of RTK into UWB indoor positioning, deploys reference stations with known precise positions, calculates measurement errors and sends them to mobile stations, and the mobile stations use the error correction information to correct their own distance measurement results, effectively offsetting the systematic errors and some environmental errors in UWB indoor positioning, thereby improving positioning accuracy and stability. At the same time, the present invention optimizes reference station deployment, error modeling and correction, data transmission, etc., so that the method and system can adapt to different indoor scenarios and have broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 Schematic diagram of the positioning method of the present invention;

[0072] Figure 2 This is a workflow diagram of the positioning method of the present invention;

[0073] Figure 3 Schematic diagram of the indoor positioning scenario of the present invention. DETAILED DESCRIPTION

[0074] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0075] Example

[0076] like Figure 1The figure shows a UWB indoor positioning method based on RTK differential technology, which includes a base station (anchor point), a reference station, and a rover. The base station transmits UWB signals, providing information for the base and rover stations to calculate their positions. The base station is deployed at a known precise location indoors and measures the distance to other base stations and rover stations, calculates the error, and transmits error correction information. The rover station receives the UWB signals and error correction information from the base station, corrects its own distance measurement results, and calculates its own position.

[0077] like Figure 2 The following is a workflow of a UWB indoor positioning method based on RTK differential thinking according to the present invention, wherein the specific steps are as follows:

[0078] Step 1: Deploy multiple reference stations with known precise coordinates indoors. The reference stations are UWB anchor points, and their positions are pre-calibrated through laser mapping.

[0079] The deployment of the base station meets the following conditions: the position is stable in the long term and fixed by bolts; there is as little obstruction as possible between the base station and the mobile station, or the non-line-of-sight error can be compensated through environmental modeling; in complex environments, the distance between base stations does not exceed 10 meters to improve error correlation.

[0080] Step 2: The base station measures the distance to other anchor points and the rover in real time, calculates the difference between the measured distance and the actual distance, and establishes an error model;

[0081] The error model includes systematic error and environmental error. Systematic error includes clock drift error and hardware delay error, and environmental error includes multipath error and non-line-of-sight error.

[0082] Assume error model for:

[0083]

[0084] in, is the systematic error, is the environmental error.

[0085] Systematic error The expression is:

[0086]

[0087] in, is the clock drift error, is the hardware delay error.

[0088] The clock drift error is calculated by the cross-correlation algorithm between the reference stations. Assume that the signal sequence received by the reference station A is , the signal sequence received by the reference station B is ,in Then, the clock drift is analyzed by calculating the cross-correlation function of the two signal sequences. The calculation formula is:

[0089]

[0090] in, Indicates the relative displacement between signal sequences, and N is the total number of sampling points. The value of , traverse all possible displacement situations, and find the corresponding value when the cross-correlation function reaches the maximum value Value, recorded as .

[0091] Since the time deviation caused by clock drift will be reflected in the relative displacement of the signal sequence, The clock drift error between reference stations A and B can be calculated. Assuming the sampling interval is , then the clock drift error It can be expressed as: .

[0092] The hardware delay error is pre-calibrated to .

[0093] Multipath effect errors and non-line-of-sight errors can be identified through signal strength and channel impulse response analysis, and Kalman filter residual analysis can be used to dynamically adjust the correction weights. The specific algorithm is as follows:

[0094] Environmental error The expression is:

[0095]

[0096] in, is the peak ratio of CIR, is the scene coefficient, which is calibrated through experiments.

[0097] CIR peak ratio and signal strength threshold judgment:

[0098] Viewing distance: and ;

[0099] Weak multipath: and ;

[0100] Strong multipath / non-line-of-sight: or ;

[0101] in, is the peak ratio of CIR, is the attenuation of signal strength, It is the maximum attenuation of signal strength under line of sight obtained by measuring the attenuation of signal strength multiple times.

[0102] Peak Ratio The formula is:

[0103]

[0104] in, is the energy of the first peak in CIR, the direct wave energy, is the total energy of all peaks in CIR, The number of identifiable peak values ​​in the CIR.

[0105] Signal strength attenuation The formula is:

[0106]

[0107] in, is the reference intensity under the preset line-of-sight environment, is the UWB signal receiving strength.

[0108] The state equation and observation equation of the Kalman filter model in Kalman filter residual analysis are:

[0109]

[0110]

[0111] in, for The estimated state value at time t, for The optimal state estimate at time , is the state transition matrix, is the process noise, for The measured value at the moment, is the anchor point coordinate, is the observation noise.

[0112] residual The formula is:

[0113]

[0114] in, is the observation value predicted based on the state at the previous moment;

[0115] Covariance matrix of the residuals for:

[0116]

[0117] in, is the observation matrix, is the predicted state covariance, is the observation noise covariance;

[0118] Correction weight Dynamic adjustment formula:

[0119]

[0120] in, is the initial weight, based on the CIR peak ratio set up: , that is, in line-of-sight environment , strong multipath , is the adjustment coefficient, is the trace of the residual covariance matrix.

[0121] Step 3: The base station encapsulates the error model into a differential frame and sends it to the mobile station via UWB;

[0122] The differential frame includes a timestamp, a reference station ID, a correction parameter, and a check bit.

[0123] Step 4: The mobile station receives the error model and corrects the distance measurement results between itself and each anchor point;

[0124] The formula for the mobile station to correct the distance measurement result is:

[0125]

[0126] in, is the corrected distance, To measure distance, The amount of error calculated for the reference station.

[0127] In step 5, the mobile station calculates its own position based on the corrected distance using the weighted least squares method. The objective function is:

[0128]

[0129] in, is the number of anchor points involved in positioning, ω a is the correction weight of the a-th anchor point. The coordinates of the mobile station are solved by this objective function as (x, y).

[0130] like Figure 3 Shown is a plan view of indoor positioning according to a preferred embodiment of the present invention.

[0131] First, base stations are deployed at four corners to transmit UWB signals. Two reference stations are deployed at precisely known locations indoors. These stations consist of a UWB module, a high-precision crystal oscillator, a temperature and humidity sensor, and a communication module. The UWB module transmits and receives UWB signals, the high-precision crystal oscillator (frequency stability <1ppm) reduces clock drift, the temperature and humidity sensor monitors the impact of environmental parameters on signal propagation speed, and the communication module transmits error correction information. A mobile station moves from left to right, consisting of both a UWB module and a communication module. The UWB module receives UWB signals and measures distance, while the communication module receives error correction information from the base stations.

[0132] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A UWB indoor positioning method based on RTK differential concept, comprising a base station, a reference station and a mobile station, characterized in that: The specific steps include: Step 1: Send UWB signals through the base station and deploy multiple reference stations with known precise coordinates indoors. The reference stations are UWB anchor points, and their positions are pre-calibrated through laser mapping; The base station is used to send UWB signals; The reference station is deployed at a known precise location indoors to measure the distance to other anchor points and mobile stations, calculate errors and send error correction information; Step 2: The base station measures the distance to other anchor points and the rover in real time, calculates the difference between the measured distance and the actual distance, and establishes an error model; Step 3: The base station sends the error model to the mobile station; The mobile station is used to receive the error correction information sent by the reference station, correct its own distance measurement result, and calculate its own position; Step 4: The mobile station receives the error model and corrects the distance measurement results between itself and each anchor point; Step 5: The mobile station calculates its own position based on the corrected distance using the weighted least squares method.

2. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: The reference station includes a UWB module, a high-precision crystal oscillator, a temperature and humidity sensor, and a communication module. The UWB module is used to send and receive UWB signals and measure distance. The high-precision crystal oscillator is used to reduce clock drift errors. The temperature and humidity sensor is used to monitor environmental parameters. The communication module is used to send error correction information.

3. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: The mobile station includes a UWB module and a communication module. The UWB module is used to receive UWB signals and measure distances, and the communication module is used to receive error correction information sent by a reference station.

4. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: In step 1, the deployment of the reference station meets the following conditions: the position is stable in the long term and fixed by bolts; there is as little obstruction as possible between the reference station and the mobile station, or the non-line-of-sight error can be compensated through environmental modeling; in a complex environment, the distance between the reference stations does not exceed 10 meters.

5. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: In step 2, the error model includes systematic error and environmental error. The systematic error includes clock drift error and hardware delay error. The environmental error includes multipath effect error and non-line-of-sight error. for: in, is the systematic error, is the environmental error.

6. The UWB indoor positioning method based on RTK differential concept according to claim 5, characterized in that: The clock drift error is calculated by the cross-correlation algorithm between the reference stations, and the hardware delay error is pre-calibrated by loopback testing. The specific algorithm is as follows: Systematic error The expression is: in, is the clock drift error, is the hardware delay error; The clock drift error is calculated by the cross-correlation algorithm between the reference stations. Assume that the signal sequence received by the reference station A is The signal sequence received by reference station B is ,in Represents the serial number of the sampling point, and then the clock drift is analyzed by calculating the cross-correlation function of the two signal sequences. The calculation formula is: in, Represents the relative displacement between signal sequences, is the total number of sampling points, by adjusting The value of , traverse all possible displacement situations, and find the corresponding value when the cross-correlation function reaches the maximum value Value, recorded as ; Since the time deviation caused by clock drift will be reflected in the relative displacement of the signal sequence, The clock drift error between reference stations A and B can be calculated, assuming the sampling interval is , then the clock drift error It can be expressed as: ; The hardware delay error is pre-calibrated to .

7. The UWB indoor positioning method based on RTK differential concept according to claim 5, characterized in that: The multipath effect error and non-line-of-sight error are identified by signal strength and channel impulse response analysis, and the correction weights are dynamically adjusted using Kalman filter residual analysis. The specific algorithm is as follows: Environmental error The expression is: in, is the peak ratio of CIR, is the scene coefficient, calibrated through experiments; CIR peak ratio and signal strength threshold judgment: Viewing distance: and ; Weak multipath: and ; Strong multipath / non-line-of-sight: or ; in, is the peak ratio of CIR, is the attenuation of signal strength, It is the maximum attenuation of signal strength under line of sight obtained by measuring the attenuation of signal strength multiple times; Peak Ratio The formula is: in, is the energy of the first peak in CIR, the direct wave energy, is the total energy of all peaks in CIR, is the number of identifiable peaks in the CIR; Signal strength attenuation The formula is: in, is the reference intensity under the preset line-of-sight environment, is the UWB signal receiving strength; The state equation and observation equation of the Kalman filter model in Kalman filter residual analysis are: in, for The estimated state value at time t, for The optimal state estimate at time , is the state transition matrix, is the process noise, for The measured value at the moment, is the anchor point coordinate, is the observation noise; residual The formula is: in, is the observation value predicted based on the state at the previous moment; Covariance matrix of the residuals for: in, is the observation matrix, is the predicted state covariance, is the observation noise covariance; Correction weight Dynamic adjustment formula: in, is the initial weight, based on the CIR peak ratio set up: , that is, in line-of-sight environment , strong multipath , is the adjustment coefficient, is the trace of the residual covariance matrix.

8. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: In the step three, the reference station encapsulates the error model into a differential frame and sends it to the mobile station via UWB. The differential frame includes a timestamp, a reference station ID, a correction parameter, and a check bit.

9. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: In step 4, the formula used by the mobile station to correct the distance measurement result is: in, is the corrected distance, To measure distance, The amount of error calculated for the reference station.

10. The UWB indoor positioning method based on RTK differential concept according to claim 1, characterized in that: In step 5, the mobile station calculates its own position using the weighted least squares method based on the corrected distance, and the objective function is: in, is the number of anchor points involved in positioning, For the The correction weight of the anchor point is used to solve the mobile station coordinates (x, y) through the objective function.

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