An asynchronous implementation method for wireless positioning system synchronization

Abstract

The present invention discloses an asynchronous implementation method for wireless positioning system synchronization, which includes that each base station broadcasts ranging signals to a mobile tag in turn using multiple directional antennas and receives feedback, measures the intensity of the feedback signal received by each antenna and the first multipath delay spread, determines the antenna priority according to a preset weight, selects the high-priority antenna, the mobile tag and the selected base station perform two-way ranging using the high-priority antenna, records the time through multiple round trips to calculate the flight time, obtains the distance from the base station, repeats the ranging to obtain the interval distance data between the mobile tag and each base station, the base station receives the positioning signal and records the time, calculates the correction and compensation terms to obtain the optimized time difference, each base station shares the received time information, combines the optimized time difference to calculate the final time difference and converts it into a distance difference, assigns weights to the distance and distance difference data according to the error characteristics, constructs an equation and a function iterative solution using the weighted least squares method, and obtains the terminal coordinates to achieve positioning.

Description

Technical Field

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

[0002] In a non-line-of-sight environment, while the wireless signal propagates between the transmitter and the receiver, 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 wireless positioning system synchronization.

[0005] The technical solution adopted by the present invention is as follows:

[0006] An asynchronous implementation method for wireless positioning system synchronization includes the following steps:

[0007] Step 1, each base station is equipped with multiple directional antennas, and successively broadcasts ranging signals to the mobile tag through each directional antenna and receives the feedback signal of the mobile tag;

[0008] 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 the high-priority antenna for ranging with the mobile tag;

[0009] Step 3, based on the high-priority antenna determined in Step 2, the mobile tag and the selected base station perform two-way ranging, with multiple signal round trips and record the corresponding times. Calculate the signal flight time through the recorded times, and then obtain the distance between the mobile tag and the base station;

[0010] Step 4, repeat Step 3 to obtain the distance data between the mobile tag and each base station;

[0011] Step 5, each base station receives the positioning signal of the mobile tag through the corresponding high-priority antenna and records the reception time. 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;

[0012] Step 6: Each base station shares the received time information 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.

[0013] 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.

[0014] 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 magnetic declination change rate exceeds the threshold, return to Step 1 to re-screen the antenna.

[0015] Preferably, measuring the first multipath delay spread includes the following:

[0016] The feedback signal received by the base station is sampled, 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.

[0017] Preferably, Step 5 further includes the following:

[0018] During the bilateral two-way ranging process between the mobile tag and a certain base station, if a frame of data transmission 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.

[0019] 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 substituting into the formula to obtain the optimized time difference includes the following:

[0020] 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;

[0021] 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;

[0022] Substitute each correction term and compensation term into the final time difference calculation formula to obtain the optimized time difference for the positioning signal sent by the mobile tag to reach different base stations.

[0023] Preferably, the conversion of the final time difference into a distance difference includes the following:

[0024] Each base station multiplies the calculated final time difference by the electromagnetic wave propagation rate, thereby converting the time difference into a corresponding distance difference.

[0025] The beneficial effects of the present invention are at least one of the following:

[0026] By optimizing the selection of directional antennas and combining two-way bilateral ranging and asynchronous time synchronization optimization, the influence of multipath effects and signal interference in a non-line-of-sight environment is effectively reduced. At the same time, by comprehensively using the directly measured distance values and distance differences in the positioning calculation, the positioning accuracy is improved, and the mobile tag can be accurately positioned in a complex non-line-of-sight environment.

[0027] By 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

[0028] Figure 1 It is a schematic flowchart of the method according to Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0030] Embodiment 1 provides an asynchronous implementation method for wireless positioning system synchronization, as Figure 1 shown, including the following steps:

[0031] 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;

[0032] Exemplarily, in a specific implementation process, each base station (denoted as A1, A2, A3, A4) is 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 a directional antenna to broadcast a ranging signal to the mobile tag and receives the feedback signal of the mobile tag.

[0033] 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 the high-priority antenna for ranging with the mobile tag;

[0034] Exemplarily, measure the signal strength Q1 and the first multipath delay spread Z1 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.

[0035] In a possible implementation, measuring the first multipath delay spread includes the following:

[0036] The feedback signal received by the base station is sampled, 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.

[0037] 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 width of the correlation peak , and through the formula (where is a coefficient related to system parameters and can be determined through system calibration) for calculation.

[0038] Step 3: Based on the high-priority antenna determined in Step 2, the mobile tag and the selected base station perform bilateral 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 through the recorded times, and then the distance between the mobile tag and the base station is obtained.

[0039] Step 4: Repeat Step 3 to obtain the distance data between the mobile tag and each base station.

[0040] Exemplarily, the mobile tag performs bilateral two-way ranging with a selected base station (such as A1). The mobile tag sends data and records the time , the base station A1 receives and records the time , the base station A1 transmits the data back and records the time , and the mobile tag receives and records the time ; then perform the second round trip and record , , , four times. Use the formula to calculate the time of flight, and then obtain the distance between the mobile tag and the base station according to d = × c (where c is the electromagnetic wave propagation rate). Repeat this process to complete the ranging operation between the mobile tag and the four base stations (A1, A2, A3, A4), and obtain the distances d1, d2, d3, d4 between the mobile tag and each base station.

[0041] Step 5: Each base station receives the positioning signal of the mobile tag through the corresponding high-priority antenna and records the reception time. 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.

[0042] In a possible implementation manner, 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 content:

[0043] 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;

[0044] Calculate the multipath correction term according to the second multipath delay spread, calculate the scenario 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;

[0045] 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.

[0046] Exemplarily, four base stations use the Kalman filtering algorithm to estimate the processing delay C1(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 scenario 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.

[0047] Exemplarily, taking base stations A1 and A2 as an example, the optimized time difference when the positioning signal sent by the mobile tag reaches different base stations is obtained

[0048]

[0049] where is the moment when base station receives the positioning signal sent by the mobile tag, is the corresponding multipath correction term of base station , is the clock offset compensation term, is the processing delay of base station at moment t, is the corresponding scenario propagation correction term of base station , is base station The moment of receiving the positioning signal sent by the mobile tag is the multipath correction term corresponding to the base station is the processing delay of the base station at time t is the scene propagation correction term corresponding to the base station 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 stations A1 and A2 respectively, obtained through the time of flight in two-way ranging and the electromagnetic wave propagation rate Calculated (that is , , , , and 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 of the signal arriving at different base stations by correcting the received signal times of different base stations.

[0050] Step 6: Each base station shares the received time information recorded by itself with each other. Combining with the optimized time difference obtained in Step 5, calculates the final time difference of the mobile tag positioning signal arriving at different base stations through a preset algorithm, and converts the final time difference into a distance difference.

[0051] In a possible implementation manner, the conversion of the final time difference into a distance difference includes the following:

[0052] 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.

[0053] 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, allocate weights based on the measurement error characteristics, construct an error equation and an objective function using the weighted least squares method, and perform iterative solution to obtain the coordinates of the mobile tag and achieve positioning.

[0054] Exemplarily, the mobile tag emits a positioning signal, and four base stations (A1, A2, A3, A4) respectively receive the signal and record the arrival times , , , . After internal processing by each base station, the time information is shared through mutual communication. Using the optimized time difference obtained in Step 3 ​​, calculate the final time difference between the positioning signals sent by the mobile tag when reaching different base stations by combining the moments when each base station receives the signals. . Taking base stations A1 and A2 as examples, the calculation formula is:

[0055]

[0056] 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. The multilateration algorithm based on the weighted least squares method is adopted. Let the coordinates of the mobile tag be , and the coordinates of base station be . Taking the distance and the distance difference as the observed values to construct the error equation:

[0057]

[0058] where and are the 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 indexes, and the value range is 1, 2, 3, 4, corresponding to base stations A1, A2, A3, and A4 respectively. < : Ensure to 4.

[0059] Meanwhile, considering the distance difference constraint, construct the objective function , perform minimization on it, and obtain the coordinates of the mobile tag through iterative calculation, completing the real-time positioning of the mobile tag. By comprehensively using the directly measured distance values and the distance differences calculated based on the time differences, and combining the weighted least squares method for positioning calculation, the positioning accuracy in the non-line-of-sight environment is effectively improved.

[0060] In a possible implementation manner, step 2 further includes: real-time monitoring of the signal intensity standard deviation and the magnetic declination change rate of each base station's directional antenna during the process of receiving the feedback signal. If the signal intensity standard deviation or the magnetic declination change rate exceeds the threshold, return to step 1 to re-screen the antenna.

[0061] Exemplarily, the standard deviation of the real-time monitored signal strength and the rate of change of magnetic declination If is greater than the preset standard deviation threshold or is greater than the preset rate of change threshold, trigger an omnidirectional scan to reselect the antenna. Select the antenna with the highest priority for subsequent ranging and positioning, and switch through an electronic switch.

[0062] In a possible implementation manner, step 5 further includes the following content:

[0063] 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 data still fails to be transmitted after waiting for the second duration for the timeout, switch to the backup ranging mode.

[0064] Exemplarily, specify a master base station (such as A1) to allocate dynamic time slots for the mobile tag and the other three base stations (A2, A3, A4) 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 A2), if the data transmission of a certain frame times out, wait for the first duration t1 for the first timeout, and wait for the second duration t2 for the second timeout. If the data still fails to be transmitted after waiting for the second duration t2 for the timeout, switch to the backup ranging mode (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.

[0065] During the bilateral two-way ranging process, a countermeasure 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 mode 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 bilateral two-way ranging and ensuring the reliability and stability of the positioning system in a non-line-of-sight environment.

[0066] 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 re-screened to ensure the stability of the 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.

[0067] 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. This operation is repeated to obtain the distance data between the mobile tag and each base station, providing a basis for subsequent positioning calculations.

[0068] 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. Based on 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.

[0069] 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, based on 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.

[0070] 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 be made, and these all belong to the protection scope of the present invention.

Claims

1. An asynchronous implementation method for wireless positioning system synchronization, characterized in that, It includes the following steps: Step 1: Each base station is equipped with multiple directional antennas. The ranging signals are broadcast to the mobile tag through each directional antenna in turn, and the feedback signals from the mobile tag are received. Step 2: For the feedback signals received by each antenna, measure their signal strength and the first multipath delay spread, then determine the antenna priority according to a preset weight ratio, and select the high-priority antenna for ranging with the mobile tag. Measure the signal strength Q1 received by each antenna and the first multipath delay spread Z 1， Calculate the priority according to the priority calculation formula , and the priority calculation formula is: is the maximum value of the received signal strength of all antennas, is the minimum value of the multipath delay spread of all antennas; 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. The signals travel back and forth multiple times and the corresponding times are recorded. The time of flight of the signal is calculated based on the recorded time, and then the distance between the mobile tag and the base station is obtained. 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 reception time. 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. The process 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 includes 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 scenario 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 arrives at different base stations. Step 6: Each base station shares the received time 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 arrives at different base stations through a preset algorithm, and converts the final time difference into a distance difference. 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, allocate weights based on the measurement error characteristics, use the weighted least squares method to construct an error equation and an objective function, and perform iterative solution to obtain the coordinates of the mobile tag and achieve positioning.

2. The asynchronous implementation method for synchronization of a wireless positioning system according to claim 1, wherein Step 2 further includes: Real-time monitoring the signal strength standard deviation and the magnetic declination change rate of each base station's directional antenna during the process of receiving feedback signals. If the signal strength standard deviation or the magnetic declination change rate exceeds the threshold, return to Step 1 to re-screen the antenna.

3. An asynchronous implementation method for wireless positioning system synchronization according to claim 2, characterized in that Measuring the first multipath delay spread includes the following: The feedback signals received by the base station are sampled, the cyclic prefix and the local standard cyclic prefix are extracted for correlation operation, 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.

4. An asynchronous implementation method for synchronizing a wireless positioning system according to claim 3, characterized in that, Step 5 further includes the following: During the two-way ranging process between the mobile tag and a certain base station, if a certain frame of data transmission 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.

5. An asynchronous implementation method for wireless positioning system synchronization according to claim 1, characterized in that, The process of converting 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.

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