Asynchronous implementation method for synchronization of wireless positioning system

Abstract

The invention discloses an asynchronous implementation method for synchronization of a wireless positioning system, which comprises the following steps that: each base station uses a plurality of directional antennas to sequentially broadcast ranging signals to a mobile tag and receive feedback, measures the strength of each antenna for receiving a feedback signal and first multipath time delay extension, determines the priority of the antennas according to a preset weight, selects a high-priority antenna, and transmits the high-priority antenna to the mobile tag; the method comprises the following steps: carrying out bilateral bidirectional distance measurement on a mobile tag and a selected base station by using a high-priority antenna, calculating flight time by multiple round-trip recording time to obtain a distance between the mobile tag and the selected base station, carrying out repeated distance measurement, obtaining interval distance data between the mobile tag and each base station, recording time when the base station receives a positioning signal, calculating correction and compensation items, and obtaining an optimized time difference; and each base station shares receiving time information, calculates a final time difference in combination with the optimized time difference, converts the final time difference into a distance difference, distributes weights for distance and distance difference data according to error characteristics, constructs an equation by using a weighted least square method, and performs function iterative solution to obtain a terminal coordinate so as to realize positioning.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless positioning, and in particular to an asynchronous implementation method for synchronizing a wireless positioning system. Background Art

[0002] In a non-line-of-sight environment, while a wireless signal propagates between a transmitting end and a receiving end, it is reflected, scattered, and diffracted by obstacles such as buildings and terrain, which makes the signal propagation path extremely complex. In such a complex non-line-of-sight environment, the wireless positioning accuracy drops sharply, making it difficult to meet the requirements of practical applications.

[0003] In terms of asynchronous synchronization mechanisms, traditional methods often rely on high-precision synchronous clocks or complex synchronization protocols, which not only greatly increase the power consumption and cost of the system, but also make it difficult to compensate for clock offsets and process delays in real time and accurately in scenarios where terminals move frequently. Summary of the Invention

[0004] To solve the technical problems existing in the prior art, the present invention provides an asynchronous implementation method for synchronizing a wireless positioning system.

[0005] The technical solution adopted by the present invention is as follows: An asynchronous implementation method for synchronizing a wireless positioning system includes the following steps: Step 1, each base station is equipped with multiple directional antennas, and sequentially broadcasts ranging signals to a mobile tag through each directional antenna and receives the feedback signal of the mobile tag; Step 2, for the feedback signal received by each antenna, measure its signal strength and the first multipath delay spread, and then determine the antenna priority according to a preset weight ratio, and select a high-priority antenna for ranging with the mobile tag; Step 3, based on the high-priority antenna determined in Step 2, the mobile tag and the selected base station carry out two-way ranging, with the signal traveling back and forth multiple times and recording the corresponding time, calculate the signal flight time through the recorded time, and then obtain the distance between the mobile tag and the base station; Step 4, repeat Step 3 to obtain the distance data between the mobile tag and each base station; Step 5, each base station receives the positioning signal of the mobile tag through the corresponding high-priority antenna and records the receiving moment, each base station uses the Kalman filtering algorithm to estimate the processing delay, obtains relevant parameters, calculates the correction term and the compensation term, and substitutes them into the formula to obtain the optimized time difference; Step 6, each base station shares the received moment information with each other, combines the optimized time difference obtained in Step 5, calculates the final time difference when the positioning signal of the mobile tag reaches different base stations through a preset algorithm, and converts the final time difference into a distance difference; Step 7: Based on the distance data between the mobile tag obtained in Step 4 and each base station, and the distance differences obtained in Step 6, assign weights according to the measurement error characteristics, construct an error equation and an objective function using the weighted least squares method, perform iterative calculations, and obtain the coordinates of the mobile tag to achieve positioning.

[0006] Preferably, Step 2 further includes: real-time monitoring of the signal strength standard deviation and magnetic declination change rate of each base station's directional antenna during the reception of the feedback signal. If the signal strength standard deviation or the magnetic declination change rate exceeds the threshold, return to Step 1 to re-screen the antenna.

[0007] Preferably, measuring the first multipath delay spread includes the following: The feedback signal received by the base station is sampled and processed, the cyclic prefix is extracted and correlated with the local standard cyclic prefix, and according to the width of the correlation peak obtained after the operation, the first multipath delay spread is calculated through a preset calculation formula.

[0008] Preferably, Step 5 further includes the following: During the bilateral two-way ranging process between the mobile tag and a certain base station, if the data transmission of a certain frame times out, wait for the first duration for the first timeout, wait for the second duration for the second timeout. If the transmission still fails after waiting for the second duration, switch to the backup ranging mode.

[0009] Preferably, each base station estimates and processes the delay using the Kalman filter algorithm, obtains relevant parameters, calculates the correction term and the compensation term, and substitutes them into the formula to obtain the optimized time difference, including the following: Each base station uses the Kalman filter algorithm to estimate the processing delay in real time, and obtains the second multipath delay spread, the incident angle deviation, and the crystal oscillator frequency deviation parameters; Calculate the multipath correction term according to the second multipath delay spread, calculate the scene propagation correction term according to the incident angle deviation, and calculate the clock offset compensation term according to the crystal oscillator frequency deviation and the synchronization time; Substitute each correction term and compensation term into the final time difference calculation formula to obtain the optimized time difference when the positioning signal sent by the mobile tag reaches different base stations.

[0010] Preferably, the conversion of the final time difference to the distance difference includes the following: Each base station multiplies the calculated final time difference by the electromagnetic wave propagation rate, thereby converting the time difference into the corresponding distance difference.

[0011] The beneficial effects of the present invention are at least one of the following: By optimizing the directional antenna selection and combining the bilateral two-way ranging and asynchronous time synchronization optimization, the influence of multipath effect and signal interference in the non-line-of-sight environment is effectively reduced. At the same time, by comprehensively using the directly measured distance value and distance difference in the positioning calculation, the positioning accuracy is improved, and the mobile tag can be accurately positioned in the complex non-line-of-sight environment.

[0012] Using the asynchronous time synchronization optimization method, the dependence on expensive external synchronization devices is avoided, and the system cost is reduced. Brief Description of the Drawings

[0013] Figure 1 It is a schematic flow chart of the method according to the first embodiment of the present invention. Detailed Embodiments

[0014] The embodiments of the present invention will be described in detail below with reference to the drawings.

[0015] Embodiment 1 provides an asynchronous implementation method for wireless positioning system synchronization, as Figure 1 shown, including the following steps: Step 1, each base station is equipped with multiple directional antennas, and sequentially broadcasts ranging signals to the mobile tag through each directional antenna, and receives the feedback signal of the mobile tag; Exemplarily, in the specific implementation process, each base station (set as A 1 、A 2 、A 3 、A 4 ) is respectively equipped with 6 directional antennas, each antenna has an angle of 60°, and only one antenna works each time. After the system is started, each base station sequentially selects one directional antenna to broadcast ranging signals to the mobile tag and receives the feedback signal of the mobile tag.

[0016] Step 2, for the feedback signal received by each antenna, measure its signal strength and the first multipath delay spread, and then determine the antenna priority according to the preset weight ratio, and select the high-priority antenna for ranging with the mobile tag; Exemplarily, measure the signal strength Q 1 and the first multipath delay spread Z 1 received by each antenna. According to the priority calculation formula , is the maximum value of the signal strength received by all antennas, is the minimum value of the multipath delay spread of all antennas, calculate the priority. Arrange all antennas in descending order according to the calculated priority, and select the antenna with the highest priority as the antenna for ranging with the mobile tag.

[0017] In a possible implementation manner, measuring the first multipath delay spread includes the following contents: The feedback signal received by the base station is sampled, the cyclic prefix is extracted and correlated with the local standard cyclic prefix, and the first multipath delay spread is calculated through a preset calculation formula according to the correlation peak width obtained after the operation.

[0018] Exemplarily, using the calculation method of the cyclic prefix, the feedback signal received by the base station is sampled, the cyclic prefix is extracted and correlated with the local standard cyclic prefix to obtain the correlation peak width , and through the formula (where is a coefficient related to system parameters and can be determined through system calibration) for calculation.

[0019] Step 3: Based on the high-priority antenna determined in Step 2, the mobile tag and the selected base station perform two-way ranging. The signal travels back and forth multiple times and the corresponding times are recorded. The time of flight of the signal is calculated from the recorded times, and then the distance between the mobile tag and the base station is obtained.

[0020] Step 4: Repeat Step 3 to obtain the distance data between the mobile tag and each base station.

[0021] Exemplarily, the mobile tag performs two-way ranging with a selected base station (such as A 1 ). The mobile tag sends data and records the moment , and base station A 1 receives and records the moment , base station A 1 sends back data and records the moment , and the mobile tag receives and records the moment ; then a second round trip is made, and , , , four moments are recorded. The formula is used to calculate the time of flight, and then the distance between the mobile tag and the base station is obtained according to d = × c (where c is the electromagnetic wave propagation rate). This process is repeated to complete the ranging operation between the mobile tag and four base stations (A 1 , A 2 , A 3 , A 4 ), and the distances d 1 , d 2 , d 3 , d 4 between the mobile tag and each base station are obtained.

[0022] Step 5: Each base station receives the positioning signal of the mobile tag through the corresponding high-priority antenna and records the reception moment. Each base station uses the Kalman filtering algorithm to estimate the processing delay, obtains relevant parameters, calculates the correction term and the compensation term, and substitutes them into the formula to obtain the optimized time difference.

[0023] In a possible implementation, each base station estimates the processing delay using the Kalman filtering algorithm, obtains relevant parameters, calculates the correction term and the compensation term, and substitutes them into the formula to obtain the optimized time difference, including the following: Each base station uses the Kalman filtering algorithm to estimate the processing delay in real time, and obtains the second multipath delay spread, the incident angle deviation, and the crystal oscillator frequency deviation parameters; Calculate the multipath correction term according to the second multipath delay spread, calculate the scene propagation correction term based on the incident angle deviation, and calculate the clock offset compensation term according to the crystal oscillator frequency deviation and the synchronization time; Substitute each correction term and compensation term into the final time difference calculation formula to obtain the optimized time difference when the positioning signal sent by the mobile tag reaches different base stations.

[0024] Exemplarily, four base stations use the Kalman filtering algorithm to estimate the processing delay C 1 (t) in real time, and obtain the second multipath delay spread , the incident angle deviation , and the crystal oscillator frequency deviation parameters. Calculate the multipath correction term according to the second multipath delay spread; calculate the scene propagation correction term based on the incident angle deviation; calculate the clock offset compensation term according to the crystal oscillator frequency deviation 10 and the synchronization time T ( is the nominal frequency of the crystal oscillator). Substitute each correction term and compensation term into the final time difference calculation formula to obtain the optimized time difference when the positioning signal sent by the mobile tag reaches different base stations.

[0025] Exemplarily, taking base station A 1 and A 2 as an example, the optimized time difference when the positioning signal sent by the mobile tag reaches different base stations is obtained

[0026]

[0027] Among them, is the moment when base station receives the positioning signal sent by the mobile tag, is the multipath correction term corresponding to base station , is the clock offset compensation term, is the processing delay of base station at moment t, is the scene propagation correction term corresponding to base station , is base station The moment when the positioning signal sent by the mobile tag is received is the base station corresponding multipath correction term is the base station processing delay at time t is the base station corresponding scene propagation correction term and Based on the two-way ranging time equivalence calculation, for example (This is an example method for calculating the transmission and reception times based on the two-way ranging time equivalence), and are the distances between the mobile tag and base station A 1 、A 2 respectively, obtained by multiplying the time of flight in the two-way ranging by the electromagnetic wave propagation rate Calculated (i.e., , , , The calculation method is the same). This formula comprehensively considers the influence of factors such as multipath effect, clock offset, and processing delay on the signal propagation time, and obtains a more accurate time difference for the signal to reach different base stations by correcting the received signal times of different base stations.

[0028] Step 6: Each base station shares the received time information recorded by itself with each other. Combining the optimized time difference obtained in Step 5, the final time difference for the positioning signal of the mobile tag to reach different base stations is calculated through a preset algorithm, and the final time difference is converted into a distance difference.

[0029] In a possible implementation manner, the conversion of the final time difference into a distance difference includes the following: Each base station multiplies the calculated final time difference by the electromagnetic wave propagation rate, thereby converting the time difference into the corresponding distance difference.

[0030] Step 7: According to the distance data between the mobile tag and each base station obtained in Step 4 and the distance difference obtained in Step 6, weights are assigned based on the measurement error characteristics, and an error equation and an objective function are constructed using the weighted least squares method for iterative solution to obtain the coordinates of the mobile tag and achieve positioning.

[0031] Exemplarily, the mobile tag transmits a positioning signal, and four base stations (A 1 、A 2 、A 3 、A 4 ) receive the signal and record the arrival times 、 、 、 After internal processing, each base station shares time information through mutual communication. Using the optimized time difference obtained in Step 3 , combined with the moments when each base station receives the signal, calculate the final time difference between the positioning signals sent by the mobile tag when reaching different base stations . Taking base station A 1 and A 2 as an example, the calculation formula is:

[0032] The time differences obtained through multiple base stations , combined with the electromagnetic wave propagation rate calculate the distance differences between the mobile tag and different base stations . Then, combined with the distances between the mobile tag and each base station , , , and the distance differences perform positioning calculations. Adopt a multilateration algorithm based on weighted least squares. Let the coordinates of the mobile tag be , and the coordinates of base station be . Taking the distance and the distance difference as observed values, construct an error equation:

[0033] where and are weight coefficients, which need to be determined according to the actual situation. For example, the appropriate weight values can be determined by testing the influence degrees of distances and distance differences on the positioning accuracy in different environments through multiple experiments are all base station indices, and the value range is 1, 2, 3, 4, corresponding to base stations A 1 , A 2 , A 3 , A 4 , < : Ensure to 4

[0034] At the same time, considering the distance difference constraint, construct an objective function , minimize it, and obtain the coordinates of the mobile tag through iterative calculation to complete the real-time positioning of the mobile tag. By comprehensively using the directly measured distance values and the distance differences calculated based on time differences, and combining the weighted least squares method for positioning calculation, the positioning accuracy in non-line-of-sight environments is effectively improved

[0035] In a possible implementation, step 2 further includes: real-time monitoring of the standard deviation of the signal strength and the change rate of the magnetic declination of each base station's directional antenna during the reception of the feedback signal. If the standard deviation of the signal strength or the change rate of the magnetic declination exceeds the threshold, return to step 1 to re-screen the antenna.

[0036] Exemplarily, real-time monitoring of the standard deviation of the signal strength and the change rate of the magnetic declination , if is greater than the preset standard deviation threshold or is greater than the preset change rate threshold, trigger an omnidirectional scan to re-select the antenna. Select the antenna with the highest priority for subsequent ranging and positioning, and switch through an electronic switch.

[0037] In a possible implementation, step 5 further includes the following: During the bilateral two-way ranging process between the mobile tag and a certain base station, if the data transmission of a certain frame times out, wait for the first duration for the first timeout, and wait for the second duration for the second timeout. If the transmission still fails after waiting for the second duration, switch to the backup ranging method.

[0038] Exemplarily, specify a master base station (such as A 1 ), and allocate dynamic time slots for the mobile tag and the other three base stations (A 2 , A 3 , A 4 ) according to the number and working status of the terminals (mobile tags and other base stations) in the positioning system. During the bilateral two-way ranging process between the mobile tag and a certain base station (such as A 2 ), if the data transmission of a certain frame times out, wait for the first duration t 1 for the first timeout, and wait for the second duration t 2 for the second timeout. If the transmission still fails after waiting for the second duration t 2 , switch to the backup ranging method (which can be selected according to the actual situation, such as one-way two-way ranging, etc.). Real-time monitor the response time difference in the bilateral two-way ranging. If it is greater than the preset time difference threshold, automatically adjust the processing delay of the device.

[0039] During the bilateral two-way ranging process, a coping strategy is formulated for data transmission timeout, such as waiting for a specific duration for the first timeout, doubling the waiting duration for the second timeout, and switching to the backup ranging method after multiple timeouts. At the same time, real-time monitor the response time difference and automatically adjust the device processing delay, effectively improving the success rate of the bilateral two-way ranging and ensuring the reliability and stability of the positioning system in a non-line-of-sight environment.

[0040] In summary, each base station is equipped with multiple directional antennas. After the system starts, each antenna is used in turn to broadcast a ranging signal to the mobile tag and receive the feedback signal. By measuring the strength of the feedback signal and the first multipath delay spread, the priority of each antenna is calculated according to the preset weight ratio, and the antenna with the highest priority is selected for subsequent ranging with the mobile tag. At the same time, the standard deviation of the signal strength and the change rate of the magnetic declination are monitored in real time. If they exceed the threshold, the antenna is reselected to ensure stable signal quality. By optimizing the selection of directional antennas, combined with the optimization of two-way bilateral ranging and asynchronous time synchronization, the influence of multipath effects and signal interference in non-line-of-sight environments is effectively reduced. In the positioning calculation, the directly measured distance value and the distance difference calculated based on the time difference are comprehensively used to improve the positioning accuracy and enable accurate positioning of the mobile tag in complex non-line-of-sight environments.

[0041] Based on the selected high-priority antenna, the mobile tag performs two-way bilateral ranging with the base station. By recording the time for multiple signal round trips, the signal flight time is calculated, and then the distance between the mobile tag and the base station is obtained. Repeat this operation to obtain the distance data between the mobile tag and each base station, providing a basis for subsequent positioning calculations.

[0042] The base station uses the Kalman filter algorithm to estimate the processing delay and obtain parameters such as the second multipath delay spread, the incident angle deviation, and the crystal oscillator frequency deviation. According to these parameters, the multipath correction term, the scenario propagation correction term, and the clock offset compensation term are calculated and substituted into the time difference calculation formula. Considering factors such as multipath effects, clock offset, and processing delay, the optimized time difference for the mobile tag positioning signal to reach different base stations is obtained.

[0043] Each base station shares the recorded reception time information. Combining the optimized time difference, the final time difference for the mobile tag positioning signal to reach different base stations is calculated through a preset algorithm and converted into a distance difference. Finally, according to the measurement error characteristics, weights are assigned to the distance data and the distance difference between the mobile tag and each base station. The weighted least squares method is used to construct an error equation and an objective function, and iterative solution is performed to obtain the coordinates of the mobile tag and achieve positioning.

[0044] The above-described embodiments only represent the specific implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the patent of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. A method for asynchronously implementing synchronization of a wireless positioning system, characterized in that: The following steps are involved: Step 1: Each base station is equipped with multiple directional antennas, broadcasts ranging signals to mobile tags through each directional antenna in turn, and receives feedback signals from mobile tags; Step 2: for the feedback signal received by each antenna, measure its signal strength and the first multipath delay spread, then determine the antenna priority according to a preset weight ratio, and select a high priority antenna for ranging with the mobile tag; Step 3: Based on the high priority antenna determined in step 2, the mobile tag conducts bilateral two-way ranging with the selected base station, performs multiple round trips and records the corresponding time, calculates the signal flight time by recording the time, and then obtains the distance between the mobile tag and the base station; Step 4, repeat step 3 to obtain the distance data between the mobile tag and each base station; Step 5: Each base station receives the positioning signal of the mobile tag through the corresponding high-priority antenna and records the receiving time. Each base station uses the Kalman filter algorithm to estimate the processing delay, obtain relevant parameters, calculate the correction term and the compensation term, and substitute them into the formula to obtain the optimized time difference; Step 6: Each base station shares its own recorded reception time information with each other, and calculates the final time difference of the mobile tag positioning signal reaching different base stations through a preset algorithm in combination with the optimized time difference obtained in step 5, and converts the final time difference into a distance difference; Step 7: Based on the distance data between the mobile tag and each base station obtained in step 4 and the distance difference obtained in step 6, weights are assigned according to the measurement error characteristics, and the error equation and objective function are constructed using the weighted least squares method. The coordinates of the mobile tag are obtained and positioning is achieved by performing iterative calculations.

2. The asynchronous implementation method of a wireless positioning system synchronization according to claim 1, characterized in that: The step 2 also includes: real-time monitoring of the signal strength standard deviation and magnetic declination change rate of each base station directional antenna in the process of receiving feedback signals, if the signal strength standard deviation or magnetic declination change rate exceeds a threshold, returning to step 1 to re-screen the antenna.

3. The asynchronous implementation method of a wireless positioning system synchronization according to claim 2, characterized in that: Measuring the first multipath delay spread includes the following: The feedback signal received by the base station is sampled and processed, a cyclic prefix is ​​extracted and correlated with a local standard cyclic prefix, and a first multipath delay spread is calculated using a preset calculation formula according to a correlation peak width obtained after the calculation.

4. The asynchronous implementation method of wireless positioning system synchronization according to claim 3, characterized in that: The step 5 also includes the following contents: During bilateral two-way ranging between a mobile tag and a base station, if a frame of data transmission times out, the first time it times out, it waits for a first time length, and then times out again, it waits for a second time length. If the transmission is still not successful after the second time length, it switches to the backup ranging mode.

5. The asynchronous implementation method of wireless positioning system synchronization according to claim 1, characterized in that: Each base station estimates the processing delay using the Kalman filter algorithm, obtains relevant parameters, calculates the correction term and the compensation term, and substitutes them into the formula to obtain the optimized time difference, which includes the following contents: Each base station estimates the processing delay in real time using the Kalman filter algorithm to obtain the second multipath delay spread, incident angle deviation and crystal oscillator frequency deviation parameters; Calculate the multipath correction term according to the second multipath delay spread, calculate the scene propagation correction term according to the incident angle deviation, and calculate the clock offset compensation term according to the crystal oscillator frequency deviation and the synchronization time; Substitute various correction items and compensation items into the final time difference calculation formula to obtain the optimized time difference between the positioning signal sent by the mobile tag and reaching different base stations.

6. The asynchronous implementation method of wireless positioning system synchronization according to claim 1, characterized in that: The conversion of the final time difference into a distance difference comprises the following steps: Each base station multiplies the calculated final time difference by the electromagnetic wave propagation velocity, thereby converting the time difference into a corresponding distance difference.

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