A high-precision positioning method and system of 5G and beidou satellite signal fusion

Abstract

This invention discloses a high-precision positioning method and system that integrates 5G and BeiDou satellite signals, belonging to the field of high-precision positioning technology. The method includes: synchronously acquiring BeiDou carrier phase, pseudorange observations, 5G downlink TOA ranging, and two types of signal characteristic data; obtaining BeiDou and 5G ranging data through satellite multipath and base station delay error models respectively; identifying satellite visibility and base station signal strength based on the two types of signal characteristics, and dynamically allocating BeiDou and 5G positioning weights; substituting the corrected ranging data and dynamic weights into the BeiDou-5G joint observation equation for solution, and then obtaining the final positioning result through optimal estimation using an improved Kalman filter. This scheme takes environmental perception and dynamic weight allocation as its core, combines dual-source ranging error correction and filtering optimization, fully adapts to real-time changes in signal quality under different scenarios, and comprehensively utilizes the positioning observation characteristics of BeiDou satellites and 5G base stations, effectively improving the accuracy of positioning output across all scenarios.

Description

Technical Field

[0001] This invention belongs to the field of high-precision positioning technology, specifically relating to a high-precision positioning method and system that integrates 5G and BeiDou satellite signals. Background Technology

[0002] With the cross-regional circulation and large-scale operation of power batteries and energy storage batteries, the demand for battery asset anti-theft and full-process security management continues to increase. Beidou satellite positioning can provide all-domain spatial location information, and 5G communication has stable and high-speed data transmission capabilities. However, a single positioning and communication mode is difficult to adapt to the full-scenario management and control needs of batteries. Therefore, a high-precision positioning method that integrates 5G and Beidou satellite signals is proposed. Based on the integrated positioning, the accurate location of batteries can be collected and the operating status can be uploaded in real time, supporting the implementation of battery asset traceability, anti-theft, and full life-cycle security management.

[0003] Existing BeiDou and 5G integrated positioning solutions rely on BeiDou satellites for outdoor wide-area positioning calculations and 5G communication base stations to supplement ranging observation data in obstructed areas to obtain location information. Then, a fixed weight is used to perform weighted fusion of the two positioning results to complete the integration processing of the two types of positioning output results. Some solutions also use basic error correction algorithms to reduce the position offset caused by single signal interference. With the complementary characteristics of satellite full coverage and 5G to make up for signal blind spots in indoor tunnels, they are widely used in various industry scenarios that require seamless and accurate positioning.

[0004] However, in the actual application of the above-mentioned fusion positioning method, the signal quality is different in different application scenarios. The location observation data output by the two types of positioning sources, Beidou satellite and 5G base station, will have different inherent deviations. The existing fusion uses fixed weights to complete the weighted calculation of the two types of positioning data. The accuracy of the final output location data will continue to decrease with the fluctuation of scene signal, making it difficult to stably output high-precision positioning results. Summary of the Invention

[0005] The purpose of this invention is to solve the problem of low positioning accuracy caused by the use of fixed weight fusion of satellite and 5G positioning data in the context of dynamic signal fluctuations in multiple scenarios. Therefore, this invention proposes a high-precision positioning method and system that fuses 5G and BeiDou satellite signals.

[0006] In a first aspect of this invention, a high-precision positioning method integrating 5G and BeiDou satellite signals is first proposed, the method comprising: Simultaneously collect BeiDou carrier phase observations, BeiDou pseudorange observations, 5G downlink TOA ranging data, satellite signal characteristic data, and 5G signal characteristic data; The BeiDou carrier phase observation value and the BeiDou pseudorange observation value are input into a preset satellite multipath effect error model to obtain BeiDou ranging data; The 5G downlink TOA ranging data is input into a preset base station side delay error model to obtain 5G ranging data; The number of visible satellites and the signal strength of 5G base stations in the current environment are identified based on the satellite signal characteristic data and the 5G signal characteristic data. The BeiDou positioning weight and the 5G positioning weight are obtained by weighting the number of visible satellites and the signal strength of 5G base stations. The BeiDou ranging correction data, the 5G ranging correction data, the BeiDou positioning weight, and the 5G positioning weight are input into the preset BeiDou-5G joint observation equation to obtain the joint observation equation result; The results of the joint observation equations are input into an improved Kalman filter for optimal estimation to obtain the localization result.

[0007] Optionally, inputting the BeiDou carrier phase observations and the BeiDou pseudorange observations into a preset satellite multipath effect error model to obtain BeiDou ranging data includes: Obtain the satellite elevation angle and azimuth angle of the target satellite corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value; Based on the satellite elevation angle and the azimuth angle, determine the target grid points corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value in the preset half-sky spatial domain grid; Extract the multipath error correction values ​​corresponding to the target grid points; the multipath error correction values ​​include carrier phase multipath correction values ​​and pseudorange multipath correction values; The carrier phase correction value is obtained by correcting the BeiDou carrier phase observation value based on the carrier phase multipath correction value. The pseudorange correction value is obtained by correcting the BeiDou pseudorange observation value based on the pseudorange multipath correction value. The consistency of the carrier phase correction value and the pseudorange correction value is checked to obtain the BeiDou ranging data.

[0008] This scheme relies on matching satellite elevation angle and azimuth angle with grid points in the semi-celestial spatial domain to accurately extract corresponding multipath error correction values. It then completes the error correction of BeiDou carrier phase and pseudorange observation values, and finally filters reliable observation data through consistency verification. This can accurately offset the ranging deviation caused by satellite multipath effect, filter abnormal observation data, and ensure that the output BeiDou ranging data has higher observation reliability and accuracy.

[0009] Optionally, inputting the 5G downlink TOA ranging data into a preset base station-side delay error model to obtain 5G ranging data includes: Determine the base station location coordinates, base station model information, and channel response estimation sequence of the target base station corresponding to the 5G downlink TOA ranging data; Extract the transmit delay calibration value and receive delay calibration value corresponding to the target base station from the preset base station hardware parameter library; The arrival time and signal power of the first path, as well as the arrival time and signal power of each reflection path, are extracted from the channel response estimation sequence. The relative time delay difference between the arrival time of the first path and the arrival time of each reflection path is calculated to obtain a sequence of relative time delay difference values; The total power of the reflection path is obtained by summing the signal power of all reflection paths, and the ratio of the signal power of the first reflection path to the total power of the reflection path is taken as the power ratio. The 5G ranging data is obtained by correcting the 5G downlink TOA ranging data based on the relative delay difference sequence and the power ratio.

[0010] This solution combines base station hardware calibration delay, channel multipath delay, and power characteristics to perform layered correction of 5G downlink TOA ranging data. It matches dedicated transmit and receive delay calibration values ​​according to the base station model, and then completes ranging compensation by distinguishing the arrival time of the first path and the reflection path, quantifying the multipath interference level by signal power, and so on. This can accurately eliminate the ranging error caused by the inherent delay of the base station hardware and multiple reflection paths, significantly reduce the system deviation of the original 5G ranging data, and output high-precision, low-noise 5G ranging data.

[0011] Optionally, the BeiDou positioning weight and 5G positioning weight are obtained by weighting the number of visible satellites and the signal strength of the 5G base station, including: Construct a two-dimensional space with the number of visible satellites as the horizontal axis and the signal strength of 5G base stations as the vertical axis; Based on historical data, BeiDou reference points and 5G reference points are set in the two-dimensional signal space; the horizontal coordinate of the BeiDou reference point is greater than the horizontal coordinate of the 5G reference point; the vertical coordinate of the BeiDou reference point is less than the vertical coordinate of the 5G reference point. The number of visible satellites and the signal strength of the 5G base station are mapped to the current signal point in the two-dimensional space; Using the BeiDou reference point and the 5G reference point as two foci, an ellipse passing through the current signal point is constructed. The BeiDou positioning weight is determined based on the ellipse and the current signal point, and the 5G positioning weight is obtained by subtracting the BeiDou positioning weight from one.

[0012] This scheme constructs a two-dimensional signal space consisting of the number of visible satellites and the signal strength of 5G base stations. Based on historical observation data, reference points for two types of positioning sources are delineated, and the real-time environmental signal state is mapped to spatial signal points. Then, an ellipse passing through the current signal point is constructed with the two reference points as the focus to complete the weight calculation. This can accurately quantify the real-time quality difference between BeiDou and 5G signals, dynamically generate positioning fusion weights adapted to the current environment, and allow the positioning source with better signal quality to obtain a higher fusion ratio. This fully leverages the observation advantages of the two types of positioning sources, weakens the interference of poor signals on the fusion positioning results, and ensures the rationality of multi-source positioning data fusion from the weight allocation level.

[0013] Optionally, determining the BeiDou positioning weights based on the ellipse and the current signal point includes: pass Calculate the BeiDou positioning weights; among which, The distance between the current signal point and the BeiDou reference point. The distance between the current signal point and the 5G reference point. The length of the major axis of the ellipse is given. It is half the distance between the BeiDou reference point and the 5G reference point.

[0014] This solution can accurately quantify the relative quality of current BeiDou and 5G signals. The weight values ​​change smoothly and continuously with the real-time signal environment, avoiding positioning jump problems caused by sudden weight changes. The weight allocation logic conforms to the signal distribution law of two-dimensional signal space. It can output accurate fusion weights adapted to real-time scenarios, ensuring the smooth and reliable weighted fusion process of multi-source positioning data, and effectively improving the continuity and accuracy of the final positioning results.

[0015] In a second aspect of this invention, a high-precision positioning system integrating 5G and BeiDou satellite signals is proposed, comprising: The acquisition module is used to simultaneously acquire BeiDou carrier phase observations, BeiDou pseudorange observations, 5G downlink TOA ranging data, satellite signal characteristic data, and 5G signal characteristic data; The first data generation module is used to input the BeiDou carrier phase observation value and the BeiDou pseudorange observation value into a preset satellite multipath effect error model to obtain BeiDou ranging data. The second data generation module is used to input the 5G downlink TOA ranging data into a preset base station side delay error model to obtain 5G ranging data. The weight generation module is used to identify the number of visible satellites and the signal strength of 5G base stations in the current environment based on the satellite signal feature data and the 5G signal feature data, and to perform weight allocation based on the number of visible satellites and the signal strength of 5G base stations to obtain the BeiDou positioning weight and the 5G positioning weight. The equation result generation module is used to input the BeiDou ranging correction data, the 5G ranging correction data, the BeiDou positioning weight and the 5G positioning weight into the preset BeiDou-5G joint observation equation to obtain the joint observation equation result; The positioning result generation module is used to input the results of the joint observation equation into an improved Kalman filter for optimal estimation to obtain the positioning result.

[0016] Optionally, the first data generation module includes: The acquisition module is used to acquire the satellite elevation angle and azimuth angle of the target satellite corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value; The grid point determination module is used to determine the target grid points corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value in a preset half-sky spatial domain grid based on the satellite elevation angle and the azimuth angle. The modified value generation module is used to extract the multipath error correction value corresponding to the target grid point; the multipath error correction value includes carrier phase multipath correction value and pseudorange multipath correction value; The first correction module is used to correct the BeiDou carrier phase observation value based on the carrier phase multipath correction value to obtain the carrier phase correction value; The second correction module is used to correct the BeiDou pseudorange observation value based on the pseudorange multipath correction value to obtain the pseudorange correction value. The BeiDou data generation module is used to perform consistency checks on the carrier phase correction value and the pseudorange correction value to obtain BeiDou ranging data.

[0017] Optionally, the second data generation module includes: The data determination module is used to determine the base station location coordinates, base station model information, and channel response estimation sequence of the target base station corresponding to the 5G downlink TOA ranging data; The extraction module is used to extract the transmit delay calibration value and receive delay calibration value corresponding to the target base station from the preset base station hardware parameter library; The estimation module is used to extract the arrival time of the first path, the signal power of the first path, and the arrival time and signal power of each reflection path based on the channel response estimation sequence. The first calculation module is used to calculate the relative time delay difference between the arrival time of the first path and the arrival time of each reflection path to obtain a relative time delay difference sequence. The second calculation module is used to calculate the sum of the signal power of all reflection paths to obtain the total power of the reflection paths, and to use the ratio of the signal power of the first path to the total power of the reflection paths as the power ratio. The third correction module is used to correct the 5G downlink TOA ranging data according to the relative delay difference sequence and the power ratio to obtain 5G ranging data.

[0018] Optionally, the weight generation module includes: The first building module is used to construct a two-dimensional space with the number of visible satellites as the horizontal axis and the 5G base station signal strength as the vertical axis; The setting module is used to set BeiDou reference points and 5G reference points in the two-dimensional signal space based on historical data; the horizontal coordinate of the BeiDou reference point is greater than the horizontal coordinate of the 5G reference point; the vertical coordinate of the BeiDou reference point is less than the vertical coordinate of the 5G reference point. The mapping module is used to map the number of visible satellites and the signal strength of the 5G base station to the current signal point in the two-dimensional space; The second construction module is used to construct an ellipse passing through the current signal point, with the BeiDou reference point and the 5G reference point as two foci. The weight determination module is used to determine the BeiDou positioning weight based on the ellipse and the current signal point, and to subtract the BeiDou positioning weight from one to obtain the 5G positioning weight.

[0019] Optionally, the weight determination module includes: pass Calculate the BeiDou positioning weights; among which, The distance between the current signal point and the BeiDou reference point. The distance between the current signal point and the 5G reference point. The length of the major axis of the ellipse is given. It is half the distance between the BeiDou reference point and the 5G reference point.

[0020] The beneficial effects of this invention are as follows: This solution takes dynamic weight allocation based on environmental perception as its core, combines dual-source ranging error correction and filtering optimization, fully adapts to the real-time changing signal quality under different scenarios, and comprehensively utilizes the positioning observation characteristics of Beidou satellites and 5G base stations to significantly reduce the interference of signal fluctuations on positioning results, effectively improving the accuracy of positioning output in all scenarios. Attached Figure Description

[0021] The present invention will now be further described with reference to the accompanying drawings.

[0022] Figure 1 A flowchart illustrating a high-precision positioning method that integrates 5G and BeiDou satellite signals, provided in an embodiment of the present invention; Figure 2 A flowchart of weight allocation provided for embodiments of the present invention. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0024] Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] The battery housing has a dedicated mounting cavity to fix the integrated terminal, which combines the BeiDou positioning module and the 5G communication module, inside the cavity. BeiDou receiving antennas and 5G transceiver antennas are respectively deployed on the outside of the battery housing to ensure signal reception. The main control unit built into the battery synchronously collects BeiDou satellite positioning information and 5G base station ranging data and completes joint calculation and fusion. The battery itself provides continuous power to the entire terminal. The high-precision location data generated by fusion is then transmitted outward through the 5G channel. The high-precision positioning achieved by the battery and the complete set of hardware is realized through the fusion of 5G and BeiDou signals.

[0026] This invention provides a high-precision positioning method that integrates 5G and BeiDou satellite signals. See also... Figure 1 The method includes the following steps: S101 synchronously collects BeiDou carrier phase observations, BeiDou pseudorange observations, 5G downlink TOA ranging data, satellite signal characteristic data, and 5G signal characteristic data; S102, input the BeiDou carrier phase observation value and the BeiDou pseudorange observation value into the preset satellite multipath effect error model to obtain BeiDou ranging data; S103, input the 5G downlink TOA ranging data into the preset base station side delay error model to obtain 5G ranging data; S104. Based on satellite signal characteristic data and 5G signal characteristic data, identify the number of visible satellites and the signal strength of 5G base stations in the current environment, and assign weights based on the number of visible satellites and the signal strength of 5G base stations to obtain BeiDou positioning weights and 5G positioning weights. S105, input the BeiDou ranging correction data, 5G ranging correction data, BeiDou positioning weight and 5G positioning weight into the preset BeiDou 5G joint observation equation to obtain the joint observation equation result; S106. The results of the joint observation equation are input into the improved Kalman filter for optimal estimation to obtain the positioning result.

[0027] In one implementation, the satellite signal characteristic data includes satellite ephemeris data and carrier-to-noise ratio (CNR) measurements for each satellite. The 5G signal characteristic data includes reference signal received power measurements, reference signal received quality measurements, and signal-to-interference-plus-noise ratio (SNR) measurements. The process of identifying the number of visible satellites and the 5G base station signal strength in the current environment involves: calculating the theoretical elevation angle and theoretical azimuth angle of each satellite relative to the positioning terminal based on the satellite ephemeris data; counting the number of satellites with theoretical elevation angles greater than a preset elevation angle threshold based on the theoretical elevation angles, and using the statistical results as the number of visible satellites; calculating the satellite spatial distribution uniformity at the current moment based on the theoretical elevation angles and the azimuth angles; calculating the weighted average CNR at the current moment based on the CNR measurements; calculating the 5G signal comprehensive quality index at the current moment based on the reference signal received power measurements, reference signal received quality measurements, and SNR measurements; and converting the 5G signal comprehensive quality index into 5G base station signal strength through a preset mapping table.

[0028] In one implementation, the generation process of the joint observation equation results is as follows: First, a weight matrix P is constructed using BeiDou positioning weights and 5G positioning weights as diagonal elements. The weights corresponding to the BeiDou ranging correction data are the BeiDou positioning weights, and the weights corresponding to the 5G ranging correction data are the 5G positioning weights. The diagonal elements of the weight matrix P are arranged sequentially according to the observation order, and the off-diagonal elements are zero. Second, the BeiDou ranging correction data and 5G ranging correction data are used to form an observation value vector L. The known spatial coordinates of each satellite and each 5G base station, along with the initial approximate coordinates of the receiver, are substituted into the coefficient matrix A and the observation value calculation vector in the preset BeiDou-5G joint observation equation. The elements of the coefficient matrix A are the partial derivatives of each observation equation with respect to unknown parameters such as the receiver's three-dimensional position coordinates and the receiver clock error; then, the formula is solved according to the normal equation. Calculate the correction for unknown parameters ,in Subtract the calculated value vector from the observed value; finally, superimpose the unknown parameter correction ΔX onto the receiver's initial approximate coordinates, iterating multiple times until... If the result is less than the preset convergence threshold, the receiver's three-dimensional position coordinates and receiver clock error obtained after iterative convergence will be output as the result of the joint observation equation.

[0029] In one implementation, the improved Kalman filter, based on the original Kalman filter, sets the observation noise covariance matrix of the observation equation to be dynamically adjusted according to the BeiDou positioning weight and the 5G positioning weight. When the BeiDou positioning weight is greater than the 5G positioning weight, the observation noise variance corresponding to the BeiDou observation value is reduced to enhance the contribution of the BeiDou observation value in the measurement update. When the 5G positioning weight is greater than the BeiDou positioning weight, the observation noise variance corresponding to the 5G observation value is reduced to enhance the contribution of the 5G observation value in the measurement update. An adaptive factor is introduced into the measurement update of the improved Kalman filter. The adaptive factor is calculated in real time according to the statistical characteristics of the observation residual. When the observation residual is greater than a preset residual threshold, the adaptive factor takes a value less than 1 to weaken the influence of the current observation value on the state estimation. When the observation residual is less than or equal to the preset residual threshold, the adaptive factor takes a value of 1. The receiver clock error is included as an independent state variable in the state equation of the improved Kalman filter, so that the receiver clock error and position and velocity are synchronously recursively derived in the time update stage. The receiver clock error parameter shared by the BeiDou observation equation and the 5G observation equation obtains continuous constraint in the time domain.

[0030] In one embodiment, inputting BeiDou carrier phase observations and BeiDou pseudorange observations into a preset satellite multipath effect error model to obtain BeiDou ranging data includes: Obtain the satellite elevation angle and azimuth angle of the target satellite corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value; Based on the satellite elevation angle and azimuth angle, determine the target grid points corresponding to the BeiDou carrier phase observation values ​​and BeiDou pseudorange observation values ​​in the preset half-sky spatial domain grid. Extract the multipath error correction values ​​corresponding to the target grid points; the multipath error correction values ​​include carrier phase multipath correction values ​​and pseudorange multipath correction values; The carrier phase correction value is obtained by correcting the BeiDou carrier phase observation value based on the carrier phase multipath correction value. The pseudorange correction value is obtained by correcting the BeiDou pseudorange observation value based on the pseudorange multipath correction value. The consistency of the carrier phase correction value and pseudorange correction value is checked to obtain the BeiDou ranging data.

[0031] In one implementation, the process of generating the pre-set hemispherical spatial domain grid is as follows: First, taking the receiving antenna of the positioning terminal as the center, the hemispherical space above the receiving antenna is defined as the hemispherical spatial domain. The elevation angle is used as latitude and the azimuth angle is used as longitude. The hemispherical spatial domain is divided into multiple grid units according to a pre-set interval, which is an unequal angular interval. The division is adaptive based on the prior spatial domain distribution information of multipath error. A sparse grid is used in areas where the multipath error changes gently, and a dense grid is used in areas where the multipath error changes drastically.

[0032] Multiple sets of raw BeiDou observation data at different times were acquired by the positioning terminal at a static reference station with known precise coordinates. The raw BeiDou observation data included BeiDou carrier phase observations and BeiDou pseudorange observations. Based on the known precise coordinates of the static reference station and the known coordinates of each satellite, the theoretical distance of each satellite at each time was calculated. The carrier phase residual of each satellite at each time was obtained by subtracting the theoretical distance from the BeiDou carrier phase observations, and the pseudorange residual of each satellite at each time was obtained by subtracting the theoretical distance from the BeiDou pseudorange observations. The elevation angle and azimuth angle of each satellite at each time were calculated based on the satellite ephemeris data of each satellite at each time. The carrier phase residuals and pseudorange residuals at each time were mapped to grid cells in the hemispherical spatial domain according to their respective elevation angles and azimuth angles. The arithmetic mean of all carrier phase residuals within the same grid cell was taken as the carrier phase multipath error correction value corresponding to that grid cell. The arithmetic mean of all pseudorange residuals within the same grid cell was taken as the pseudorange multipath error correction value corresponding to that grid cell.

[0033] Finally, each grid cell and its corresponding carrier phase multipath error correction value and pseudorange multipath error correction value are associated and stored to obtain the preset half-sky spatial domain grid.

[0034] In one implementation, the carrier phase correction value is obtained by subtracting the carrier phase multipath correction value from the BeiDou carrier phase observation value, thereby eliminating the influence of multipath effect on the carrier phase observation value; the pseudorange correction value is obtained by subtracting the pseudorange multipath correction value from the BeiDou carrier phase observation value, thereby eliminating the influence of multipath effect on the carrier phase observation value.

[0035] In one implementation, when the difference between the carrier phase correction value and the pseudorange correction value is less than a preset consistency threshold, the carrier phase correction value is output as BeiDou ranging data; when the difference between the carrier phase correction value and the pseudorange correction value is greater than or equal to the preset consistency threshold, the carrier phase correction value is refixed with integer ambiguity based on the pseudorange correction value to obtain the refixed carrier phase correction value, and the refixed carrier phase correction value is output as BeiDou ranging data.

[0036] In one embodiment, inputting 5G downlink TOA ranging data into a preset base station-side delay error model to obtain 5G ranging data includes: Determine the base station location coordinates, base station model information, and channel response estimation sequence of the target base station corresponding to the 5G downlink TOA ranging data; Extract the transmit delay calibration value and receive delay calibration value corresponding to the target base station from the preset base station hardware parameter library; The arrival time and signal power of the first path, as well as the arrival time and signal power of each reflection path, are extracted from the channel response estimation sequence. The relative time delay difference sequence is obtained by calculating the relative time delay difference between the arrival time of the first path and the arrival times of each reflection path. The total power of the reflection path is obtained by summing the signal power of all reflection paths, and the ratio of the signal power of the first reflection path to the total power of the reflection path is taken as the power ratio. 5G ranging data is obtained by correcting the 5G downlink TOA ranging data based on the relative delay difference sequence and power ratio.

[0037] In one implementation, the process of correcting 5G downlink TOA ranging data based on the relative delay difference sequence and power ratio involves: performing cluster analysis on the relative delay difference sequence to divide it into dense clusters and discrete clusters; determining the primary multipath delay value based on the cluster center of the dense clusters; determining the multipath environment complexity index based on the number of discrete clusters; comparing the power ratio with a preset non-line-of-sight (NLS) determination threshold; determining the NLS propagation identifier based on the comparison result; determining the comprehensive multipath delay correction value based on the primary multipath delay value and the multipath environment complexity index; determining the NLS delay correction value based on the NLS propagation identifier; and using the transmit link delay calibration value and... The first level of correction for 5G downlink TOA ranging data is performed using the received link delay calibration value, resulting in a first TOA correction value. Next, a second level of correction is performed using the comprehensive multipath delay correction value, resulting in a second TOA correction value. Finally, a third level of correction is performed using the non-line-of-sight (NLS) delay correction value, resulting in a third TOA correction value. Multiplying the third TOA correction value by the speed of light yields the 5G ranging data. Since 5G signals are affected by three different types of errors during transmission—base station hardware fixed delay, multipath propagation delay, and NLS propagation delay—and these errors have different physical mechanisms and are independent of each other, they must be processed step-by-step rather than combined. Cluster analysis distinguishes between stable multipath and occasional interference, improving the reliability of multipath correction. Adaptive power ratio determination of the NLS state ensures that NLS correction only intervenes when necessary. The advantage of this hierarchical correction is that it ensures that each type of error is accurately subtracted at its corresponding physical level, effectively suppressing various propagation delay errors in the final 5G ranging data.

[0038] In one embodiment, see Figure 2 The BeiDou positioning weight and 5G positioning weight are obtained by weighting the number of visible satellites and the signal strength of 5G base stations. S201, constructing a two-dimensional space with the number of visible satellites as the horizontal axis and the 5G base station signal strength as the vertical axis; S202 sets up BeiDou reference points and 5G reference points in a two-dimensional signal space based on historical data; S203 maps the number of visible satellites and the signal strength of 5G base stations to the current signal point in two-dimensional space; S204, using the BeiDou reference point and the 5G reference point as two foci, constructs an ellipse passing through the current signal point; S205, determine the BeiDou positioning weight based on the ellipse and the current signal point, and subtract the BeiDou positioning weight from one to obtain the 5G positioning weight; Among them, the x-coordinate of the BeiDou reference point is greater than that of the 5G reference point; The vertical coordinate of the BeiDou reference point is smaller than that of the 5G reference point.

[0039] In one implementation, the process of determining the BeiDou reference point and the 5G reference point involves statistically analyzing historical positioning data to obtain the number of visible satellites, the 5G base station signal strength, and the corresponding positioning accuracy at each historical moment. From epochs where the positioning accuracy is better than a preset accuracy threshold, the coordinates of the BeiDou reference point are determined according to the signal characteristics corresponding to the sorting of BeiDou signal quality from high to low and 5G signal quality from low to high. The horizontal axis represents the high number of visible satellites, representing typical characteristics of scenarios where BeiDou signals are advantageous, and the vertical axis represents the low 5G base station signal strength, representing that 5G signals are typically weak in this scenario. From epochs where the positioning accuracy is better than a preset accuracy threshold, the coordinates of the BeiDou reference point are determined according to the signal characteristics corresponding to the sorting of 5G signal quality from high to low and BeiDou signal quality from low to high. The coordinates of the 5G reference points are defined, with the horizontal axis representing the number of visible satellites (low satellite visibility), indicating that the BeiDou signal is usually weaker in scenarios where the 5G signal is dominant, and the vertical axis representing the signal strength of the 5G base station (high 5G base station signal), representing typical characteristics of scenarios where the 5G signal is dominant. Using this method, the BeiDou reference point is located in the lower right region of the two-dimensional signal space (larger horizontal axis and smaller vertical axis), representing a typical scenario where the BeiDou signal is dominant and the 5G signal is weak. The 5G reference point is located in the upper left region of the two-dimensional signal space (smaller horizontal axis and larger vertical axis), representing a typical scenario where the 5G signal is dominant and the BeiDou signal is weak. The two reference points are diagonally distributed in space, allowing the current signal point at any location in the two-dimensional signal space to determine the weight allocation direction based on its relative geometric relationship with the two reference points.

[0040] In one implementation, the number of visible satellites and the signal strength of 5G base stations are two key independent variables determining the respective positioning contributions of BeiDou and 5G. These two variables constitute a two-dimensional signal space, where different regions correspond to different signal environment states. After mapping the current number of visible satellites and the 5G base station signal strength to a current signal point in the two-dimensional space, the spatial position of this point reflects the degree of signal bias between the two signals at that moment. The closer the current signal point is to the BeiDou reference point, the closer the current signal environment is to a BeiDou-advantaged scenario, and the higher the weight should be for the BeiDou positioning system; the closer the current signal point is to the 5G reference point, the closer the current signal environment is to a 5G-advantaged scenario, and the higher the weight should be for the 5G positioning system; when the current signal point is located between two reference points, the weight transitions continuously between them. An ellipse, a geometric figure whose sum of distances to its two foci is constant, is constructed by taking two reference points as foci and passing through the current signal point. The length of the ellipse's major axis reflects the overall horizontal distance from the current signal point to the two reference points. A shorter major axis indicates that the signal point is closer to the core region between the two reference points, while a longer major axis indicates that the signal point is offset towards one of the reference points. The spatial position of the current signal point can be mapped to continuous weight values ​​through the ellipse's geometric parameters. This method transforms weight allocation into a spatial geometric positioning method, allowing weight allocation to be simultaneously controlled by both the local bias of the signal point and the overall coverage level. Furthermore, the weight output is continuous, smooth, and requires no truncation.

[0041] In one embodiment, determining the BeiDou positioning weights based on the ellipse and the current signal point includes: pass Calculate the BeiDou positioning weights; among which, This represents the distance between the current signal point and the BeiDou reference point. The distance between the current signal point and the 5G reference point. Let be the length of the major axis of the ellipse. It is half the distance between the BeiDou reference point and the 5G reference point.

[0042] In one implementation, the formula transforms weight allocation into the analysis of the geometric position of the signal point in two-dimensional space, and determines the weight value by the distance relationship between the current signal point and the two reference points and the geometric parameters of the ellipse. This is used to determine which reference point the current signal point is biased towards; when the signal point is close to the BeiDou reference point... Less than When this term is positive and approaches 0.5, the weight of BeiDou increases; conversely, when this term is negative and approaches -0.5, the weight of BeiDou decreases, meaning the weight of 5G increases. The use of squared distance reflects the physical law that signal reliability decreases inversely with the square of the distance; the closer the signal source, the higher its reliability, and the reliability decreases with distance in a square-like rather than a nonlinear relationship. In this formula, when a approaches c, the factor approaches 0, the contribution of the squared distance ratio term is weakened, and the weight returns to 0.5. When a is much greater than c, the factor approaches 1, and the weight is entirely determined by the squared distance ratio term. This formula allows the weight allocation to be simultaneously controlled by both the local bias of the signal point and the overall coverage level. The local bias determines the direction of the weight, while the overall coverage determines the magnitude of the weight, thus achieving a continuous mapping from the spatial location of the signal point to the weight value.

[0043] The foregoing has described one embodiment of the present invention in detail, but this content is merely a preferred embodiment and should not be considered as limiting the scope of the present invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the scope of the claims of this invention.

Claims

1. A high-precision positioning method integrating 5G and BeiDou satellite signals, characterized in that, The method includes: Simultaneously collect BeiDou carrier phase observations, BeiDou pseudorange observations, 5G downlink TOA ranging data, satellite signal characteristic data, and 5G signal characteristic data; The BeiDou carrier phase observation value and the BeiDou pseudorange observation value are input into a preset satellite multipath effect error model to obtain BeiDou ranging data; The 5G downlink TOA ranging data is input into a preset base station side delay error model to obtain 5G ranging data; The number of visible satellites and the signal strength of 5G base stations in the current environment are identified based on the satellite signal characteristic data and the 5G signal characteristic data. The BeiDou positioning weight and the 5G positioning weight are obtained by weighting the number of visible satellites and the signal strength of 5G base stations. The BeiDou ranging correction data, the 5G ranging correction data, the BeiDou positioning weight, and the 5G positioning weight are input into the preset BeiDou-5G joint observation equation to obtain the joint observation equation result; The results of the joint observation equations are input into an improved Kalman filter for optimal estimation to obtain the localization result.

2. The high-precision positioning method based on the fusion of 5G and BeiDou satellite signals according to claim 1, characterized in that, The BeiDou carrier phase observations and the BeiDou pseudorange observations are input into a preset satellite multipath effect error model to obtain BeiDou ranging data, including: Obtain the satellite elevation angle and azimuth angle of the target satellite corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value; Based on the satellite elevation angle and the azimuth angle, determine the target grid points corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value in the preset half-sky spatial domain grid; Extract the multipath error correction values ​​corresponding to the target grid points; the multipath error correction values ​​include carrier phase multipath correction values ​​and pseudorange multipath correction values; The carrier phase correction value is obtained by correcting the BeiDou carrier phase observation value based on the carrier phase multipath correction value. The pseudorange correction value is obtained by correcting the BeiDou pseudorange observation value based on the pseudorange multipath correction value. The consistency of the carrier phase correction value and the pseudorange correction value is checked to obtain the BeiDou ranging data.

3. The high-precision positioning method based on the fusion of 5G and BeiDou satellite signals according to claim 1, characterized in that, The 5G downlink TOA ranging data is input into a preset base station-side delay error model to obtain 5G ranging data, including: Determine the base station location coordinates, base station model information, and channel response estimation sequence of the target base station corresponding to the 5G downlink TOA ranging data; Extract the transmit delay calibration value and receive delay calibration value corresponding to the target base station from the preset base station hardware parameter library; The arrival time and signal power of the first path, as well as the arrival time and signal power of each reflection path, are extracted from the channel response estimation sequence. The relative time delay difference between the arrival time of the first path and the arrival time of each reflection path is calculated to obtain a sequence of relative time delay difference values; The total power of the reflection path is obtained by summing the signal power of all reflection paths, and the ratio of the signal power of the first reflection path to the total power of the reflection path is taken as the power ratio. The 5G ranging data is obtained by correcting the 5G downlink TOA ranging data based on the relative delay difference sequence and the power ratio.

4. The high-precision positioning method based on the fusion of 5G and BeiDou satellite signals according to claim 1, characterized in that, The BeiDou positioning weight and 5G positioning weight are obtained by weighting the number of visible satellites and the signal strength of the 5G base station, including: Construct a two-dimensional space with the number of visible satellites as the horizontal axis and the signal strength of 5G base stations as the vertical axis; Based on historical data, BeiDou reference points and 5G reference points are set in the two-dimensional signal space; the horizontal coordinate of the BeiDou reference point is greater than the horizontal coordinate of the 5G reference point; the vertical coordinate of the BeiDou reference point is less than the vertical coordinate of the 5G reference point. The number of visible satellites and the signal strength of the 5G base station are mapped to the current signal point in the two-dimensional space; Using the BeiDou reference point and the 5G reference point as two foci, an ellipse passing through the current signal point is constructed. The BeiDou positioning weight is determined based on the ellipse and the current signal point, and the 5G positioning weight is obtained by subtracting the BeiDou positioning weight from one.

5. A high-precision positioning method for fusion of 5G and BeiDou satellite signals according to claim 4, characterized in that, Determining the BeiDou positioning weights based on the ellipse and the current signal point includes: pass Calculate the BeiDou positioning weights; among which, The distance between the current signal point and the BeiDou reference point. The distance between the current signal point and the 5G reference point. The length of the major axis of the ellipse is given. It is half the distance between the BeiDou reference point and the 5G reference point.

6. A high-precision positioning system integrating 5G and BeiDou satellite signals, characterized in that, The system includes: The acquisition module is used to simultaneously acquire BeiDou carrier phase observations, BeiDou pseudorange observations, 5G downlink TOA ranging data, satellite signal characteristic data, and 5G signal characteristic data; The first data generation module is used to input the BeiDou carrier phase observation value and the BeiDou pseudorange observation value into a preset satellite multipath effect error model to obtain BeiDou ranging data. The second data generation module is used to input the 5G downlink TOA ranging data into a preset base station side delay error model to obtain 5G ranging data. The weight generation module is used to identify the number of visible satellites and the signal strength of 5G base stations in the current environment based on the satellite signal feature data and the 5G signal feature data, and to perform weight allocation based on the number of visible satellites and the signal strength of 5G base stations to obtain the BeiDou positioning weight and the 5G positioning weight. The equation result generation module is used to input the BeiDou ranging correction data, the 5G ranging correction data, the BeiDou positioning weight and the 5G positioning weight into the preset BeiDou-5G joint observation equation to obtain the joint observation equation result; The positioning result generation module is used to input the results of the joint observation equation into an improved Kalman filter for optimal estimation to obtain the positioning result.

7. A high-precision positioning system integrating 5G and BeiDou satellite signals according to claim 6, characterized in that, The first data generation module includes: The acquisition module is used to acquire the satellite elevation angle and azimuth angle of the target satellite corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value; The grid point determination module is used to determine the target grid points corresponding to the BeiDou carrier phase observation value and the BeiDou pseudorange observation value in a preset half-sky spatial domain grid based on the satellite elevation angle and the azimuth angle. The modified value generation module is used to extract the multipath error correction value corresponding to the target grid point; the multipath error correction value includes carrier phase multipath correction value and pseudorange multipath correction value; The first correction module is used to correct the BeiDou carrier phase observation value based on the carrier phase multipath correction value to obtain the carrier phase correction value; The second correction module is used to correct the BeiDou pseudorange observation value based on the pseudorange multipath correction value to obtain the pseudorange correction value. The BeiDou data generation module is used to perform consistency checks on the carrier phase correction value and the pseudorange correction value to obtain BeiDou ranging data.

8. A high-precision positioning method based on the fusion of 5G and BeiDou satellite signals according to claim 6, characterized in that, The second data generation module includes: The data determination module is used to determine the base station location coordinates, base station model information, and channel response estimation sequence of the target base station corresponding to the 5G downlink TOA ranging data; The extraction module is used to extract the transmit delay calibration value and receive delay calibration value corresponding to the target base station from the preset base station hardware parameter library; The estimation module is used to extract the arrival time of the first path, the signal power of the first path, and the arrival time and signal power of each reflection path based on the channel response estimation sequence. The first calculation module is used to calculate the relative time delay difference between the arrival time of the first path and the arrival time of each reflection path to obtain a relative time delay difference sequence. The second calculation module is used to calculate the sum of the signal power of all reflection paths to obtain the total power of the reflection paths, and to use the ratio of the signal power of the first path to the total power of the reflection paths as the power ratio. The third correction module is used to correct the 5G downlink TOA ranging data according to the relative delay difference sequence and the power ratio to obtain 5G ranging data.

9. A high-precision positioning method for fusion of 5G and BeiDou satellite signals according to claim 6, characterized in that, The weight generation module includes: The first building module is used to construct a two-dimensional space with the number of visible satellites as the horizontal axis and the 5G base station signal strength as the vertical axis; The setting module is used to set BeiDou reference points and 5G reference points in the two-dimensional signal space based on historical data; the horizontal coordinate of the BeiDou reference point is greater than the horizontal coordinate of the 5G reference point; the vertical coordinate of the BeiDou reference point is less than the vertical coordinate of the 5G reference point. The mapping module is used to map the number of visible satellites and the signal strength of the 5G base station to the current signal point in the two-dimensional space; The second construction module is used to construct an ellipse passing through the current signal point, with the BeiDou reference point and the 5G reference point as two foci. The weight determination module is used to determine the BeiDou positioning weight based on the ellipse and the current signal point, and to subtract the BeiDou positioning weight from one to obtain the 5G positioning weight.

10. A high-precision positioning method based on the fusion of 5G and BeiDou satellite signals according to claim 9, characterized in that, The weight determination module includes: pass Calculate the BeiDou positioning weights; among which, The distance between the current signal point and the BeiDou reference point. The distance between the current signal point and the 5G reference point. The length of the major axis of the ellipse is given. It is half the distance between the BeiDou reference point and the 5G reference point.

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