CN-121978729-A - Positioning method, positioning device, storage medium and navigation system

CN121978729ACN 121978729 ACN121978729 ACN 121978729ACN-121978729-A

Abstract

The present disclosure relates to positioning methods, devices, storage media, and navigation systems. The positioning method comprises the steps of obtaining low-orbit satellite information and positioning system observation information corresponding to a plurality of low-orbit satellites at the current moment, conducting topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to the next moment at the current moment, conducting multi-source data fusion processing based on the satellite feature prediction matrix, the low-orbit satellite information, the positioning system observation information and a preset Kalman filter to obtain a floating point number result corresponding to the current position, and conducting positioning resolving processing based on the floating point number result and the preset ambiguity fixed model to obtain a target positioning result. The method and the device can acquire more stable and comprehensive low-orbit satellite information, perform topology modeling through the preset dynamic prediction model, overcome frequent inter-satellite link switching caused by high-speed movement of the low-orbit satellite, and ensure the stability of the positioning model in the case of topology change.

Inventors

JIN YUE
Si Shengying

Assignees

中汽创智科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260325

Claims (10)

1. A positioning method, applied to a navigation system, the navigation system including a plurality of low-orbit satellites, wherein an orbit deployment mode of the plurality of low-orbit satellites is a mixed deployment mode of polar orbit and non-polar orbit, the method comprising: acquiring multi-source observation data corresponding to the current moment, wherein the multi-source observation data comprises low-orbit satellite information and positioning system observation information corresponding to a plurality of low-orbit satellites; Performing topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to the next moment at the current moment, wherein the satellite feature prediction matrix is a matrix obtained by fusion processing based on a spatial feature matrix and a time feature matrix, the spatial feature matrix is obtained by performing spatial feature extraction based on the low-orbit satellite information, and the time feature matrix is obtained by performing time feature extraction based on the low-orbit satellite information; Performing multi-source data fusion processing based on the satellite feature prediction matrix, the low-orbit satellite information, the positioning system observation information and a preset Kalman filter to obtain a floating point number result corresponding to the current position; and carrying out positioning resolving processing based on the floating point number result, the low orbit satellite information and a preset ambiguity fixed model to obtain a target positioning result.
2. The method according to claim 1, wherein the performing topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to a next time at a current time includes: Constructing a satellite feature matrix corresponding to the current moment based on the low-orbit satellite information, wherein the satellite feature matrix is used for representing state features corresponding to the plurality of low-orbit satellites; constructing a satellite adjacency matrix based on the low-orbit satellite information, wherein the satellite adjacency matrix is used for representing the spatial dependency relationship among the plurality of low-orbit satellites; performing weighted aggregation processing based on the satellite adjacent matrix and the satellite feature matrix to obtain an initial space fusion matrix; and performing feature transformation processing based on the initial spatial fusion matrix and the spatial feature transformation matrix to obtain the spatial feature matrix.
3. The method according to claim 2, wherein the method further comprises: performing weighted aggregation processing on the time convolution kernel parameter matrix based on a preset dynamic prediction model and the satellite feature matrix to obtain an initial time fusion matrix; and performing feature transformation processing based on the initial time fusion matrix and the time feature transformation matrix to obtain the time feature matrix.
4. The method of claim 1, wherein the low-orbit satellite information includes doppler shift, and the performing multi-source data fusion processing based on the satellite feature prediction matrix, the low-orbit satellite information, the positioning system observation information and a preset kalman filter to obtain a floating point number result corresponding to the current position includes: updating a noise matrix corresponding to an observation equation in the preset Kalman filter and a constraint matrix corresponding to the observation equation based on the satellite feature prediction matrix and the Doppler frequency shift to obtain an updated observation equation and an updated constraint matrix; updating the preset Kalman filter based on the updated observation equation and the updated constraint matrix to obtain an updated preset Kalman filter; And carrying out multi-source data fusion processing based on the low-orbit satellite information, the positioning system observation information and the updated preset Kalman filter to obtain the floating point number result.
5. The method of claim 1, wherein the performing a positioning solution based on the floating point number result, the low-orbit satellite information, and a preset ambiguity fixing model to obtain a target positioning result comprises: determining a resolving state characteristic parameter based on the low-orbit satellite information, wherein the resolving state characteristic parameter is used for representing signal quality characteristics corresponding to a plurality of low-orbit satellites; Determining a verification threshold based on the floating point number result and the resolved state feature parameter; Performing evaluation processing based on the floating point number result to obtain an integer solution candidate set; the target location result is determined based on the inspection threshold and the integer solution candidate set.
6. The method of claim 5, wherein the floating point number result comprises an ambiguity parameter and a residual sequence corresponding to the ambiguity parameter, wherein the determining a verification threshold based on the floating point number result and the resolved state feature parameter comprises: extracting local features based on residual sequences corresponding to the ambiguity parameters to obtain local features; Performing time sequence feature analysis based on the ambiguity parameters and the resolving state feature parameters to obtain time sequence features; Performing fusion processing based on the local features and the time sequence features to obtain target fusion features; and performing threshold self-adaptive mapping processing on the target fusion characteristics to obtain a detection threshold.
7. The method of claim 5, wherein the integer candidate set includes an optimal candidate solution and a suboptimal candidate solution, the determining the target positioning result based on the inspection threshold and the integer solution candidate set comprising: Determining a target ratio based on the optimal candidate solution and the suboptimal candidate solution; Determining a fixed result based on the verification threshold and the target ratio; And if the fixed result is successful in fixation, carrying out position solving processing based on the optimal candidate solution and the updated observation equation to obtain the target positioning result.
8. A positioning device for use in a navigation system comprising a plurality of low-orbit satellites, the plurality of low-orbit satellites being deployed in a hybrid polar-orbit and non-polar-orbit configuration, the device comprising: The information acquisition module is used for acquiring multi-source observation data corresponding to the current moment, wherein the multi-source observation data comprises low-orbit satellite information and positioning system observation information corresponding to a plurality of low-orbit satellites; The topology modeling module is used for carrying out topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to the next moment at the current moment, wherein the satellite feature prediction matrix is a matrix obtained by fusion processing of a spatial feature matrix and a time feature matrix, the spatial feature matrix is obtained by carrying out spatial feature extraction based on the low-orbit satellite information, and the time feature matrix is obtained by carrying out time feature extraction based on the low-orbit satellite information; The floating point number resolving module is used for carrying out multi-source data fusion processing based on the satellite feature prediction matrix, the low-orbit satellite information, the positioning system observation information and a preset Kalman filter to obtain a floating point number result corresponding to the current position; And the positioning result determining module is used for carrying out positioning calculation processing based on the floating point number result, the low-orbit satellite information and a preset ambiguity fixed model to obtain a target positioning result.
9. A navigation system comprising a plurality of low-orbit satellites and the positioning device according to claim 8, wherein the orbit deployment of the plurality of low-orbit satellites is a hybrid deployment of polar and non-polar orbits.
10. A computer readable storage medium having stored therein at least one instruction or at least one program loaded and executed by a processor to implement the positioning method of any of claims 1-7.

Description

Positioning method, positioning device, storage medium and navigation system Technical Field The present disclosure relates to the field of navigation technologies, and in particular, to a positioning method, a positioning device, a storage medium, and a navigation system. Background The low-orbit satellite (Low Earth Orbit satellite, LEO) becomes a key means for improving the positioning precision and convergence speed of the global navigation satellite system (Global Navigation SATELLITE SYSTEM, GNSS) due to the characteristics of rapid geometric configuration change, strong signal power and the like. The current mainstream technical scheme comprises a joint positioning model, namely, firstly, the regional positioning capability is improved by constructing a joint observation equation of LEO and a medium-high orbit satellite. Secondly, the low orbit satellite is utilized to provide communication and navigation services at the same time, so that the problem of signal coverage in remote areas is solved, for example, a vehicle-mounted terminal forwards GNSS enhanced information through LEO to realize high-precision positioning. Thirdly, the edge artificial intelligent module is adopted to realize satellite-borne real-time object detection and data compression, and the downlink transmission delay is reduced. However, the prior art still has the following problems that (1) the quality of the observed data is unstable, the redundancy and the deletion of satellite-borne GNSS data and the capturing of high dynamic signals are difficult, and (2) LEO satellites move at a high speed relative to the ground, so that the visible arc segments of the satellites are short, the links are frequently switched, and the positioning is interrupted. Disclosure of Invention In order to solve at least one technical problem set forth above, the present disclosure proposes a positioning method, apparatus, storage medium, and navigation system. According to an aspect of the present disclosure, there is provided a positioning method applied to a navigation system, the navigation system including a plurality of low-orbit satellites, an orbit deployment mode of the plurality of low-orbit satellites being a hybrid deployment mode of polar orbit and non-polar orbit, including: acquiring multi-source observation data corresponding to the current moment, wherein the multi-source observation data comprises low-orbit satellite information and positioning system observation information corresponding to a plurality of low-orbit satellites; Performing topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to the next moment at the current moment, wherein the satellite feature prediction matrix is a matrix obtained by fusion processing based on a spatial feature matrix and a time feature matrix, the spatial feature matrix is obtained by performing spatial feature extraction based on the low-orbit satellite information, and the time feature matrix is obtained by performing time feature extraction based on the low-orbit satellite information; Performing multi-source data fusion processing based on the satellite feature prediction matrix, the low-orbit satellite information, the positioning system observation information and a preset Kalman filter to obtain a floating point number result corresponding to the current position; and carrying out positioning resolving processing based on the floating point number result, the low orbit satellite information and a preset ambiguity fixed model to obtain a target positioning result. In some possible embodiments, the performing topology modeling processing based on the low-orbit satellite information and a preset dynamic prediction model to obtain a satellite feature prediction matrix corresponding to a next moment at the current moment includes: Constructing a satellite feature matrix corresponding to the current moment based on the low-orbit satellite information, wherein the satellite feature matrix is used for representing state features corresponding to the plurality of low-orbit satellites; constructing a satellite adjacency matrix based on the low-orbit satellite information, wherein the satellite adjacency matrix is used for representing the spatial dependency relationship among the plurality of low-orbit satellites; performing weighted aggregation processing based on the satellite adjacent matrix and the satellite feature matrix to obtain an initial space fusion matrix; and performing feature transformation processing based on the initial spatial fusion matrix and the spatial feature transformation matrix to obtain the spatial feature matrix. In some possible embodiments, the method further comprises: performing weighted aggregation processing on the time convolution kernel parameter matrix based on a preset dynamic prediction model and the satellite feature matrix to obtain an init