Ionospheric-considered ambiguity fixing optimization method and device, equipment and medium

Abstract

This application discloses a method, apparatus, device, and medium for ambiguity fixing optimization considering the ionosphere, relating to the field of satellite positioning technology. The method includes: acquiring observation data of a target satellite from each base station within a detection area; repeatedly dividing all base stations into multiple triangulation units based on triangulation; constructing and solving an ionospheric delay correction model for each triangulation unit based on the observation data of each base station; determining the ionospheric delay spatial smoothness corresponding to each triangulation unit; performing ambiguity optimization on several triangulation units with an ionospheric delay spatial smoothness not less than a preset anomaly threshold based on the initial ambiguity of the target satellite, obtaining several optimized ambiguities, and fixing these optimized ambiguities as the true ambiguity values ​​of each base station for the target satellite within the corresponding triangulation unit. By implementing this application, the accuracy of base station ambiguity fixing can be improved.

Description

Technical Field

[0001] This application relates to the field of satellite positioning technology, and in particular to a method, apparatus, equipment and medium for ambiguity fixation optimization considering the ionosphere. Background Technology

[0002] In current GNSS positioning technology, the correct fixation of integer ambiguity at base stations / reference stations is fundamental for BeiDou CORS (Continuous Operational Reference System) network RTK positioning and a core prerequisite for ensuring centimeter-level positioning. During ambiguity fixation, gross errors can directly lead to a 19-57mm deviation in subsequent ionospheric delay determination, resulting in gross ionospheric delay errors. Conversely, gross ionospheric delay errors can mask ambiguity fixation anomalies, meaning optimizing these errors won't improve positioning accuracy. This combination creates a vicious cycle of "error superposition and mutual interference." Furthermore, due to the large distances between CORS reference stations, the impact of ionospheric delay cannot be ignored. Therefore, it is necessary to study integer ambiguity fixation methods under ionospheric influence.

[0003] In existing technologies, to optimize the fixing accuracy of integer ambiguities under the influence of the ionosphere, ionosphere-free delay combinations or ionosphere constraints are generally used to eliminate the influence of the ionosphere and thus fix ambiguities. However, these two methods typically rely solely on single-station residual checks during ambiguity fixing, without considering the spatial distribution patterns of the ionosphere. This results in an inability to fully utilize ionosphere modeling to optimize the ambiguity fixing process, and therefore fails to meet the practical needs of ambiguity fixing under ionospheric influence. Furthermore, these methods only consider eliminating the ionospheric influence, without considering the possibility of incorporating and repairing the ionospheric influence to reverse-engineer gross errors in ambiguity fixing. Therefore, how to improve the ambiguity fixing accuracy of base stations in satellite positioning under the influence of the ionosphere remains a pressing technical problem that needs to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, device, and medium for ambiguity fixation optimization considering the ionosphere, in order to solve the technical problem that the ambiguity fixation accuracy of existing base stations fails to meet actual requirements under the influence of the ionosphere.

[0005] According to a first aspect of the embodiments of this application, a method for fixing and optimizing ambiguity considering the ionosphere is provided, comprising: Acquire observation data of the target satellite from each base station within the area to be detected; wherein, the observation data includes carrier phase observations and integer ambiguities of the target satellite under multiple preset frequency bands; Based on triangulation, all base stations are repeatedly divided to obtain multiple triangular network units. Based on the observation data of each base station on the target satellite, an ionospheric delay correction model for each triangular mesh unit is constructed by linear fitting, and each ionospheric delay correction model is solved to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit. Based on the initial ambiguity of the target satellite, ambiguity optimization is performed on several triangulation units with ionospheric delay spatial flatness not less than a preset anomaly threshold to obtain several optimized ambiguities, and the several optimized ambiguities are fixed as the true ambiguity values ​​of each base station in the corresponding triangulation unit for the target satellite.

[0006] This application first acquires observation data of the target satellite from each base station within the area to be detected. Then, it repeatedly divides the base stations into multiple triangular mesh units using triangulation. Next, it constructs and solves the ionospheric delay correction model for each triangular mesh unit to obtain the ionospheric delay spatial smoothness of each unit through linear fitting. Then, based on the initial ambiguity of the target satellite, it performs ambiguity optimization on triangular mesh units with ionospheric delay spatial smoothness not less than an anomaly threshold, determining the corresponding ambiguity ground truth. By dividing the base stations into triangular mesh units and constructing the ionospheric delay correction model with these units as the main body, it can characterize the spatial relationship between base stations based on the triangular mesh units. This allows the constructed ionospheric delay correction model to characterize the spatial distribution pattern of the ionosphere, thus enabling the reasonable use of ionospheric influence to fix base station ambiguities and improve the accuracy of base station ambiguity fixing. Simultaneously, by optimizing triangular mesh units whose ionospheric delay spatial smoothness does not meet the condition based on the initial ambiguity of the target satellite, it can further utilize ionospheric influence to correct the base station ambiguity optimization, improving the accuracy of the obtained optimized ambiguity and thus improving the accuracy of ambiguity fixing through ambiguity optimization.

[0007] In some embodiments of this application, acquiring the observation data of each base station within the area to be detected regarding the target satellite specifically includes: Acquire initial observation data of the target satellite from each base station within the area to be detected in the multiple frequency bands; wherein, the initial observation data includes carrier phase observation values ​​of the target satellite in the multiple frequency bands; Based on the initial observation data of each base station, and using a preset integer ambiguity fixing method, the integer ambiguity of each base station for the target satellite in multiple frequency bands is calculated. Combining the initial observation data and integer ambiguity of each base station, the observation data of each base station for the target satellite is obtained.

[0008] This application first obtains the initial observation data of each base station in the area to be detected on the target satellite in multiple frequency bands. Then, based on the integer ambiguity fixing method, it calculates the integer ambiguity of each base station on the target satellite in multiple frequency bands, which can obtain the observation data of each base station on the target satellite, providing a data foundation for the subsequent establishment of an ionospheric delay correction model based on the observation data.

[0009] In some embodiments of this application, the step of constructing an ionospheric delay correction model for the target satellite for each triangular mesh unit through linear fitting based on the observation data of each base station on the target satellite specifically includes: Based on the observation data of each base station on the target satellite, the ionospheric delay of each baseline in each triangulation cell is calculated; wherein, the baseline is the connection between the master base station and each slave base station in the triangulation cell. Based on the location coordinates of each base station within each triangulation unit, construct the direction vector of each baseline within each triangulation unit; By combining the ionospheric delay and direction vector of each baseline within each triangulation cell, an ionospheric delay correction model for the target satellite is constructed for each triangulation cell through linear fitting.

[0010] This application first calculates the ionospheric delay of each baseline within each triangulation cell based on the observation data of each base station on the target satellite. Then, it constructs the direction vector of each baseline within each triangulation cell based on the position coordinates of each base station. Subsequently, it constructs an ionospheric delay correction model for each triangulation cell on the target satellite using a linear fitting method. Based on the representation of the spatial relationship between base stations by the triangulation cell, the ionospheric delay correction model constructed by linear fitting can represent the spatial distribution law of the ionosphere. This allows for the reasonable use of ionospheric influence to fix base station ambiguities and improves the accuracy of base station ambiguity fixation.

[0011] In some embodiments of this application, the step of calculating the ionospheric delay of each baseline within each triangulation cell based on the observation data of each base station on the target satellite specifically includes: Based on the observation frequency and observation wavelength of each base station in the multiple frequency bands, and combined with the carrier phase observation value and integer ambiguity of the target satellite in the multiple frequency bands, the ionospheric delay of each base station to the target satellite is calculated. Based on the primary base station at the beginning and the secondary base station at the end of each baseline within each triangulation unit, and combined with the ionospheric delay of each base station relative to the target satellite, the ionospheric delay of each baseline within each triangulation unit is obtained.

[0012] This application first calculates the ionospheric delay of each base station to the target satellite based on the observation frequency and wavelength of each base station in multiple frequency bands, combined with the carrier phase observation value and integer ambiguity of the target satellite. Then, based on the master base station at the beginning and the slave base station at the end of each baseline in each triangulation unit, the ionospheric delay of each baseline in each triangulation unit is obtained. By first calculating the ionospheric delay of each base station to the target satellite, and then calculating the ionospheric delay of each baseline based on the master base station and slave base station of each baseline in each triangulation unit, one of the representations of the spatial relationship between the base stations in the triangulation unit can be converted into a numerically calculable ionospheric delay, providing a data foundation for the subsequent construction and solution of the ionospheric delay correction model.

[0013] In some embodiments of this application, the step of solving each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit specifically includes: Each ionospheric delay correction model is solved separately to obtain the spatial gradient vector of each triangular mesh unit; wherein, the spatial gradient vector includes the spatial gradient along the meridian and the spatial gradient along the parallel; Calculate the ionospheric delay spatial flatness corresponding to each triangulation cell based on the spatial gradient vectors of all triangulation cells.

[0014] This application first solves each ionospheric delay correction model to obtain the spatial gradient vector of each triangular mesh unit, and then calculates the ionospheric delay spatial smoothness. By solving the ionospheric delay correction model, the ionospheric delay spatial smoothness can be obtained, that is, the aggregated numerical expression of the spatial relationship of each base station under the influence of the ionosphere can be obtained. Then, the influence of the ionosphere can be reasonably characterized based on the ionospheric delay spatial smoothness, so as to make reasonable use of the influence of the ionosphere to fix the ambiguity of the base station and improve the accuracy of base station ambiguity fixing.

[0015] In some embodiments of this application, the step of performing ambiguity optimization on a number of triangular mesh units whose ionospheric delay spatial flatness is not less than a preset anomaly threshold, based on the initial ambiguity of the target satellite, to obtain a number of corresponding optimized ambiguities, specifically includes: Based on the initial ambiguity of the target satellite, multiple alternative ambiguities are generated according to a preset error cycle. Based on the multiple candidate ambiguities, the ionospheric delay correction model corresponding to each anomalous triangular mesh unit is calculated respectively to obtain multiple candidate ionospheric delay spatial flatness corresponding to each anomalous triangular mesh unit; wherein, the anomalous triangular mesh unit is a triangular mesh unit whose ionospheric delay spatial flatness is not less than a preset anomalous threshold. The candidate ambiguity corresponding to the candidate ionospheric delay space flatness that meets the preset optimization conditions in each anomalous triangulation cell is taken as the optimized ambiguity of the anomalous triangulation cell; wherein, the preset optimization conditions are less than the preset anomalous threshold and have the smallest value among all candidate ionospheric delay space flatnesses in the anomalous triangulation cell.

[0016] This application first generates multiple candidate ambiguities based on the initial ambiguity of the target satellite, then recalculates the ionospheric delay correction model corresponding to each anomalous triangulation unit to obtain multiple candidate ionospheric delay spatial smoothness. Subsequently, the candidate ambiguity corresponding to the candidate ionospheric delay spatial smoothness that meets the preset optimization conditions in each anomalous triangulation unit is used as the optimized ambiguity of the anomalous triangulation unit. This can further utilize the ionospheric influence to correct the base station ambiguity optimization, improve the accuracy of the obtained optimized ambiguity, and thus improve the accuracy of ambiguity fixation through optimized ambiguity.

[0017] In some embodiments of this application, it further includes: The integer ambiguity of each base station for the target satellite within a number of triangular mesh units where the ionospheric delay spatial flatness is less than the preset anomaly threshold is fixed as the corresponding ambiguity true value.

[0018] This application fixes the integer ambiguity of each base station to the target satellite in several triangular mesh units where the ionospheric delay space flatness is less than a preset anomaly threshold as the corresponding ambiguity true value. By calculating the ionospheric delay space flatness, it verifies that there is no anomaly in the integer ambiguity of the base station to the target satellite. Thus, under the condition that the ionospheric influence does not exceed the threshold, the corresponding ambiguity true value is determined by a simple method, which is simple, fast and highly accurate.

[0019] According to a second aspect of the embodiments of this application, an ambiguity fixing and optimization device considering the ionosphere is provided, including a base station observation data acquisition module, a triangulation unit division module, an ionosphere model construction and solution module, and a base station ambiguity optimization module; The base station observation data acquisition module is used to acquire observation data of the target satellite from each base station in the area to be detected; wherein, the observation data includes carrier phase observation values ​​and integer ambiguity of the target satellite under multiple preset frequency bands; The triangulation unit division module is used to repeatedly divide all base stations based on triangulation to obtain multiple triangulation units. The ionospheric model construction and solution module is used to construct an ionospheric delay correction model for each triangular mesh unit of the target satellite based on the observation data of each base station on the target satellite through linear fitting, and to solve each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit. The base station ambiguity optimization module is used to perform ambiguity optimization on a number of triangulation units with ionospheric delay spatial flatness not less than a preset anomaly threshold according to the initial ambiguity of the target satellite, to obtain a number of optimized ambiguities, and to fix the number of optimized ambiguities as the true ambiguity values ​​of each base station for the target satellite in the corresponding triangulation unit.

[0020] In some embodiments of this application, the base station observation data acquisition module includes an initial data acquisition unit and an ambiguity resolution unit; The initial data acquisition unit is used to acquire initial observation data of the target satellite from each base station in the area to be detected under the multiple frequency bands; wherein, the initial observation data includes carrier phase observation values ​​of the target satellite under the multiple frequency bands; The ambiguity resolution unit is used to calculate the integer ambiguity of each base station for the target satellite in multiple frequency bands based on the initial observation data of each base station and a preset integer ambiguity fixing method, and to obtain the observation data of each base station for the target satellite by combining the initial observation data and integer ambiguity of each base station.

[0021] In some embodiments of this application, the ionospheric model construction and solution module includes an ionospheric delay calculation unit, a baseline direction vector calculation unit, and a delay correction model construction unit; The ionospheric delay calculation unit is used to calculate the ionospheric delay of each baseline in each triangulation cell based on the observation data of each base station on the target satellite; wherein, the baseline is the line connecting the master base station and each slave base station in the triangulation cell. The baseline direction vector calculation unit is used to construct the direction vector of each baseline in each triangulation unit based on the position coordinates of each base station in each triangulation unit. The delay correction model construction unit is used to combine the ionospheric delay and direction vector of each baseline in each triangulation unit, and construct the ionospheric delay correction model of each triangulation unit for the target satellite through linear fitting.

[0022] In some embodiments of this application, the ionospheric delay calculation unit includes a base station delay calculation subunit and a baseline delay calculation subunit; The base station delay calculation subunit is used to calculate the ionospheric delay of each base station to the target satellite based on the observation frequency and observation wavelength of each base station in the multiple frequency bands, combined with the carrier phase observation value and integer ambiguity of the target satellite in the multiple frequency bands. The baseline delay calculation subunit is used to obtain the ionospheric delay of each baseline in each triangulation unit based on the master base station at the beginning and the slave base station at the end of each baseline in each triangulation unit, combined with the ionospheric delay of each base station to the target satellite.

[0023] In some embodiments of this application, the ionosphere model construction and solution module includes a spatial gradient vector calculation unit and a spatial flatness calculation unit; The spatial gradient vector calculation unit is used to solve each ionospheric delay correction model to obtain the spatial gradient vector of each triangulation unit; wherein, the spatial gradient vector includes the spatial gradient along the meridian and the spatial gradient along the parallel. The spatial flatness calculation unit is used to calculate the ionospheric delay spatial flatness corresponding to each triangulation unit based on the spatial gradient vector of all triangulation units.

[0024] In some embodiments of this application, the base station ambiguity optimization module includes a candidate ambiguity generation unit, a candidate flatness calculation unit, and an optimized ambiguity determination unit; The alternative ambiguity generation unit is used to generate multiple alternative ambiguities based on the initial ambiguity of the target satellite and according to a preset number of error weeks. The alternative flatness calculation unit is used to solve the ionospheric delay correction model corresponding to each anomalous triangular mesh unit according to the multiple alternative ambiguities, and obtain multiple alternative ionospheric delay space flatness corresponding to each anomalous triangular mesh unit; wherein, the anomalous triangular mesh unit is a triangular mesh unit whose ionospheric delay space flatness is not less than a preset anomalous threshold. The optimized ambiguity determination unit is used to take the candidate ambiguity corresponding to the candidate ionospheric delay space flatness that meets the preset optimization conditions in each abnormal triangulation unit as the optimized ambiguity of the abnormal triangulation unit; wherein, the preset optimization conditions are less than the preset abnormal threshold and the smallest value among all candidate ionospheric delay space flatnesses in the abnormal triangulation unit.

[0025] In some embodiments of this application, a base station ambiguity determination module is also included; the base station ambiguity determination module is used to fix the integer ambiguity of each base station for the target satellite in a plurality of triangular mesh units in which the ionospheric delay spatial flatness is less than the preset anomaly threshold to the corresponding ambiguity true value.

[0026] This application first acquires observation data of the target satellite from each base station within the area to be detected. Then, it repeatedly divides the base stations into multiple triangular mesh units using triangulation. Next, it constructs and solves the ionospheric delay correction model for each triangular mesh unit to obtain the ionospheric delay spatial smoothness of each unit through linear fitting. Then, based on the initial ambiguity of the target satellite, it performs ambiguity optimization on triangular mesh units with ionospheric delay spatial smoothness not less than an anomaly threshold, determining the corresponding ambiguity ground truth. By dividing the base stations into triangular mesh units and constructing the ionospheric delay correction model with these units as the main body, it can characterize the spatial relationship between base stations based on the triangular mesh units. This allows the constructed ionospheric delay correction model to characterize the spatial distribution pattern of the ionosphere, thus enabling the reasonable use of ionospheric influence to fix base station ambiguities and improve the accuracy of base station ambiguity fixing. Simultaneously, by optimizing triangular mesh units whose ionospheric delay spatial smoothness does not meet the condition based on the initial ambiguity of the target satellite, it can further utilize ionospheric influence to correct the base station ambiguity optimization, improving the accuracy of the obtained optimized ambiguity and thus improving the accuracy of ambiguity fixing through ambiguity optimization.

[0027] According to a third aspect of the embodiments of this application, a computer device is provided, comprising: a processor; a memory; and a computer program stored in the memory and configured to be executed by the processor; wherein the processor executes the computer program to implement the ambiguity fixing optimization method considering the ionosphere described in this application.

[0028] According to a fourth aspect of the embodiments of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to execute an ionosphere-considered ambiguity fixing optimization method as described in this application. Attached Figure Description

[0029] Figure 1 This is a flowchart illustrating a method for fixing and optimizing ambiguity considering the ionosphere, as shown in certain embodiments of this application. Figure 2 This is a block diagram of a fuzziness fixation optimization device considering the ionosphere, as shown in certain embodiments of this application. Detailed Implementation

[0030] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below in conjunction with the accompanying drawings are exemplary and are only used to explain some embodiments of this application, and should not be construed as limiting the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments shown in this application without inventive effort are within the protection scope of this application.

[0031] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, unless otherwise explicitly specified, "a plurality of" or "several" means two or more.

[0032] In existing technologies, to optimize the fixing accuracy of integer ambiguities under the influence of the ionosphere, ionosphere-free delay combinations or ionosphere constraints are generally used to eliminate the influence of the ionosphere and thus fix ambiguities. However, these two methods typically rely solely on single-station residual checks during ambiguity fixing, without considering the spatial distribution patterns of the ionosphere. This results in an inability to fully utilize ionosphere modeling to optimize the ambiguity fixing process, and therefore fails to meet the practical needs of ambiguity fixing under ionospheric influence. Furthermore, these methods only consider eliminating the ionospheric influence, without considering the possibility of incorporating and repairing the ionospheric influence to reverse-engineer gross errors in ambiguity fixing. Therefore, how to improve the ambiguity fixing accuracy of base stations in satellite positioning under the influence of the ionosphere remains a pressing technical problem that needs to be solved.

[0033] Based on the above technical background, please refer to Figure 1 This application provides a method for fixing and optimizing ambiguity considering the ionosphere, including steps S101 to S104, each step of which is as follows: Step S101: Obtain observation data of the target satellite from each base station in the area to be detected; wherein, the observation data includes carrier phase observation values ​​and integer ambiguity of the target satellite under multiple preset frequency bands.

[0034] In some embodiments of this application, acquiring the observation data of each base station within the area to be detected regarding the target satellite specifically includes: Acquire initial observation data of the target satellite from each base station within the area to be detected in the multiple frequency bands; wherein, the initial observation data includes carrier phase observation values ​​of the target satellite in the multiple frequency bands; Based on the initial observation data of each base station, and using a preset integer ambiguity fixing method, the integer ambiguity of each base station for the target satellite in multiple frequency bands is calculated. Combining the initial observation data and integer ambiguity of each base station, the observation data of each base station for the target satellite is obtained.

[0035] To illustrate the ambiguity fixation optimization method considering the ionosphere provided in this application, we assume there are 6 base stations A to F in the area to be detected, the target satellite is i, and the frequency bands include the B1 and B2 bands. This will be used as an example for further explanation.

[0036] Specifically, the preset integer ambiguity fixing methods include, but are not limited to, pseudorange method, integer solution search algorithm, LAMBDA (Least-squares AMBiguity Decorrelation Adjustment) algorithm and Fast Ambiguity Decomposition (FARA) algorithm, with LAMBDA algorithm being preferred.

[0037] This application first obtains the initial observation data of each base station in the area to be detected on the target satellite in multiple frequency bands. Then, based on the integer ambiguity fixing method, it calculates the integer ambiguity of each base station on the target satellite in multiple frequency bands, which can obtain the observation data of each base station on the target satellite, providing a data foundation for the subsequent establishment of an ionospheric delay correction model based on the observation data.

[0038] Step S102: Based on triangulation, all base stations are repeatedly divided to obtain multiple triangular network units.

[0039] Specifically, when repeatedly dividing the base station based on triangulation, the Delaunay triangulation algorithm is used for division, and either the Lawson algorithm or the Bowyer-Watson algorithm can be selected.

[0040] Step S103: Based on the observation data of each base station on the target satellite, construct the ionospheric delay correction model of each triangular mesh unit for the target satellite through linear fitting, and solve each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit.

[0041] In some embodiments of this application, the step of constructing an ionospheric delay correction model for the target satellite for each triangular mesh unit through linear fitting based on the observation data of each base station on the target satellite specifically includes: Based on the observation data of each base station on the target satellite, the ionospheric delay of each baseline in each triangulation cell is calculated; wherein, the baseline is the connection between the master base station and each slave base station in the triangulation cell. Based on the location coordinates of each base station within each triangulation unit, construct the direction vector of each baseline within each triangulation unit; By combining the ionospheric delay and direction vector of each baseline within each triangulation cell, an ionospheric delay correction model for the target satellite is constructed for each triangulation cell through linear fitting.

[0042] Specifically, when calculating the ionospheric delay of a baseline within a single triangulation cell, it is necessary to first determine the ionospheric delays of the primary base station at the beginning of the baseline and the secondary base station at the end. The calculation of the ionospheric delay is the same for each type of base station. Here, we take the ionospheric delay of base station A relative to satellite i as an example, and the specific calculation formula is as follows: ; in, These are the observation frequencies for frequency bands B1 and B2, respectively. These are the observation wavelengths for frequency bands B1 and B2, respectively. Let be the integer ambiguity obtained by base station A for satellite i in frequency bands B1 and B2 respectively; These are the carrier phase observation values ​​obtained by base station A from satellite i in frequency bands B1 and B2, respectively.

[0043] Following the above calculation of the ionospheric delay of base station A to satellite i, the ionospheric delay of each base station within each triangulation cell can be calculated. Therefore, the ionospheric delay of the baseline is determined by the ionospheric delays of the two base stations at the beginning and end of the network. Taking triangulation ABC as an example, assuming the main base station is A, the baselines of triangulation ABC are AB and AC. Taking baseline AB as an example, the ionospheric delay of baseline AB is... This allows us to calculate the ionospheric delay of each baseline within each triangular mesh unit.

[0044] Specifically, when constructing the direction vector of a baseline, it is necessary to calculate it based on the position coordinates of the primary base station at the beginning of the baseline and the secondary base station at the end. The calculated direction vector includes the direction vector of the baseline along the meridian and the direction vector of the baseline along the parallel. Taking baseline AB as an example, the calculated direction vector is the direction vector of baseline AB along the meridian. and the direction vector of baseline AB along the parallel of latitude .

[0045] Specifically, taking the triangular network ABC as an example, the ionospheric delay correction model for target satellite i, constructed through linear fitting, is as follows: ; in, These represent the ionospheric delays of baselines AB and AC relative to target satellite i, respectively. These are the direction vectors of baseline AB along the meridians and parallels of latitude, respectively. These are the direction vectors of baseline AC along the meridians and parallels of latitude, respectively. These represent the spatial gradients of the target satellite i along the meridians and parallels, respectively, for the triangulation network ABC.

[0046] This application first calculates the ionospheric delay of each baseline within each triangulation cell based on the observation data of each base station on the target satellite. Then, it constructs the direction vector of each baseline within each triangulation cell based on the position coordinates of each base station. Subsequently, it constructs an ionospheric delay correction model for each triangulation cell on the target satellite using a linear fitting method. Based on the representation of the spatial relationship between base stations by the triangulation cell, the ionospheric delay correction model constructed by linear fitting can represent the spatial distribution law of the ionosphere. This allows for the reasonable use of ionospheric influence to fix base station ambiguities and improves the accuracy of base station ambiguity fixation.

[0047] In some embodiments of this application, the step of calculating the ionospheric delay of each baseline within each triangulation cell based on the observation data of each base station on the target satellite specifically includes: Based on the observation frequency and observation wavelength of each base station in the multiple frequency bands, and combined with the carrier phase observation value and integer ambiguity of the target satellite in the multiple frequency bands, the ionospheric delay of each base station to the target satellite is calculated. Based on the primary base station at the beginning and the secondary base station at the end of each baseline within each triangulation unit, and combined with the ionospheric delay of each base station relative to the target satellite, the ionospheric delay of each baseline within each triangulation unit is obtained.

[0048] This application first calculates the ionospheric delay of each base station to the target satellite based on the observation frequency and wavelength of each base station in multiple frequency bands, combined with the carrier phase observation value and integer ambiguity of the target satellite. Then, based on the master base station at the beginning and the slave base station at the end of each baseline in each triangulation unit, the ionospheric delay of each baseline in each triangulation unit is obtained. By first calculating the ionospheric delay of each base station to the target satellite, and then calculating the ionospheric delay of each baseline based on the master base station and slave base station of each baseline in each triangulation unit, one of the representations of the spatial relationship between the base stations in the triangulation unit can be converted into a numerically calculable ionospheric delay, providing a data foundation for the subsequent construction and solution of the ionospheric delay correction model.

[0049] In some embodiments of this application, the step of solving each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit specifically includes: Each ionospheric delay correction model is solved separately to obtain the spatial gradient vector of each triangular mesh unit; wherein, the spatial gradient vector includes the spatial gradient along the meridian and the spatial gradient along the parallel; Calculate the ionospheric delay spatial flatness corresponding to each triangulation cell based on the spatial gradient vectors of all triangulation cells.

[0050] Specifically, taking a triangular mesh R as an example, the ionospheric delay spatial flatness of the triangular mesh element R is calculated as follows: ; in, The spatial flatness of the ionospheric delay for the target satellite i relative to the triangular network R; The number of triangular mesh elements; These represent the spatial gradients of the triangulation network k along the meridians and parallels of the target satellite i, respectively. These represent the spatial gradients of the triangulation network R along the meridians and parallels of the target satellite i.

[0051] This application first solves each ionospheric delay correction model to obtain the spatial gradient vector of each triangular mesh unit, and then calculates the ionospheric delay spatial smoothness. By solving the ionospheric delay correction model, the ionospheric delay spatial smoothness can be obtained, that is, the aggregated numerical expression of the spatial relationship of each base station under the influence of the ionosphere can be obtained. Then, the influence of the ionosphere can be reasonably characterized based on the ionospheric delay spatial smoothness, so as to make reasonable use of the influence of the ionosphere to fix the ambiguity of the base station and improve the accuracy of base station ambiguity fixing.

[0052] Step S104: Based on the initial ambiguity of the target satellite, perform ambiguity optimization on several triangulation units with ionospheric delay spatial flatness not less than a preset anomaly threshold to obtain several optimized ambiguities, and fix the several optimized ambiguities as the true ambiguity values ​​of each base station in the corresponding triangulation unit for the target satellite.

[0053] Specifically, preset anomaly threshold The preferred value is 1 mm / km.

[0054] In some embodiments of this application, the step of performing ambiguity optimization on a number of triangular mesh units whose ionospheric delay spatial flatness is not less than a preset anomaly threshold, based on the initial ambiguity of the target satellite, to obtain a number of corresponding optimized ambiguities, specifically includes: Based on the initial ambiguity of the target satellite, multiple alternative ambiguities are generated according to a preset error cycle. Based on the multiple candidate ambiguities, the ionospheric delay correction model corresponding to each anomalous triangular mesh unit is calculated respectively to obtain multiple candidate ionospheric delay spatial flatness corresponding to each anomalous triangular mesh unit; wherein, the anomalous triangular mesh unit is a triangular mesh unit whose ionospheric delay spatial flatness is not less than a preset anomalous threshold. The candidate ambiguity corresponding to the candidate ionospheric delay space flatness that meets the preset optimization conditions in each anomalous triangulation cell is taken as the optimized ambiguity of the anomalous triangulation cell; wherein, the preset optimization conditions are less than the preset anomalous threshold and have the smallest value among all candidate ionospheric delay space flatnesses in the anomalous triangulation cell.

[0055] Specifically, the preset error cycle number is: Let the current initial ambiguity be... The alternative fuzziness is .

[0056] This application first generates multiple candidate ambiguities based on the initial ambiguity of the target satellite, then recalculates the ionospheric delay correction model corresponding to each anomalous triangulation unit to obtain multiple candidate ionospheric delay spatial smoothness. Subsequently, the candidate ambiguity corresponding to the candidate ionospheric delay spatial smoothness that meets the preset optimization conditions in each anomalous triangulation unit is used as the optimized ambiguity of the anomalous triangulation unit. This can further utilize the ionospheric influence to correct the base station ambiguity optimization, improve the accuracy of the obtained optimized ambiguity, and thus improve the accuracy of ambiguity fixation through optimized ambiguity.

[0057] In some embodiments of this application, it further includes: The integer ambiguity of each base station for the target satellite within a number of triangular mesh units where the ionospheric delay spatial flatness is less than the preset anomaly threshold is fixed as the corresponding ambiguity true value.

[0058] This application fixes the integer ambiguity of each base station to the target satellite in several triangular mesh units where the ionospheric delay space flatness is less than a preset anomaly threshold as the corresponding ambiguity true value. By calculating the ionospheric delay space flatness, it verifies that there is no anomaly in the integer ambiguity of the base station to the target satellite. Thus, under the condition that the ionospheric influence does not exceed the threshold, the corresponding ambiguity true value is determined by a simple method, which is simple, fast and highly accurate.

[0059] Compared to existing technologies, this application first acquires observation data of the target satellite from each base station within the area to be detected, and then repeatedly divides the base stations into multiple triangular mesh units through triangulation. Next, it constructs and solves the ionospheric delay correction model for each triangular mesh unit to the target satellite using linear fitting to obtain the ionospheric delay spatial smoothness of each triangular mesh unit. Then, based on the initial ambiguity of the target satellite, it performs ambiguity optimization on triangular mesh units with ionospheric delay spatial smoothness not less than an anomaly threshold to determine the corresponding ambiguity ground truth. This is achieved by dividing the base stations into triangular mesh units and constructing the ionospheric delay correction model using these triangular mesh units as the main components. The delay correction model can characterize the spatial relationship between base stations based on triangular mesh units, thereby enabling the constructed ionospheric delay correction model to characterize the spatial distribution law of the ionosphere. This allows for the reasonable use of ionospheric influence to fix base station ambiguities, improving the accuracy of base station ambiguity fixing. Simultaneously, by optimizing triangular mesh units that do not meet the conditions for ionospheric delay spatial flatness using the initial ambiguity of the target satellite, the optimization of base station ambiguities can be further corrected using ionospheric influence, improving the accuracy of the optimized ambiguity and thus enhancing the accuracy of ambiguity fixing through ambiguity optimization.

[0060] For a method corresponding to the one described above, please refer to [link / reference]. Figure 2 The present application provides an ambiguity fixing and optimization device considering the ionosphere, including a base station observation data acquisition module 210, a triangulation unit division module 220, an ionosphere model construction and solution module 230, and a base station ambiguity optimization module 240. The base station observation data acquisition module 210 is used to acquire the observation data of each base station in the area to be detected on the target satellite; wherein, the observation data includes carrier phase observation values ​​and integer ambiguity of the target satellite under multiple preset frequency bands; The triangulation unit division module 220 is used to repeatedly divide all base stations based on triangulation to obtain multiple triangulation units. The ionospheric model construction and solution module 230 is used to construct an ionospheric delay correction model for each triangular mesh unit of the target satellite based on the observation data of each base station on the target satellite through linear fitting, and to solve each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit. The base station ambiguity optimization module 240 is used to perform ambiguity optimization on a number of triangulation units whose ionospheric delay spatial flatness is not less than a preset anomaly threshold according to the initial ambiguity of the target satellite, to obtain a number of optimized ambiguities, and to fix the number of optimized ambiguities as the true ambiguity values ​​of each base station for the target satellite in the corresponding triangulation unit.

[0061] In some embodiments of this application, the base station observation data acquisition module 210 includes an initial data acquisition unit and an ambiguity resolution unit; The initial data acquisition unit is used to acquire initial observation data of the target satellite from each base station in the area to be detected under the multiple frequency bands; wherein, the initial observation data includes carrier phase observation values ​​of the target satellite under the multiple frequency bands; The ambiguity resolution unit is used to calculate the integer ambiguity of each base station for the target satellite in multiple frequency bands based on the initial observation data of each base station and a preset integer ambiguity fixing method, and to obtain the observation data of each base station for the target satellite by combining the initial observation data and integer ambiguity of each base station.

[0062] In some embodiments of this application, the ionospheric model construction and solution module 230 includes an ionospheric delay calculation unit, a baseline direction vector calculation unit, and a delay correction model construction unit; The ionospheric delay calculation unit is used to calculate the ionospheric delay of each baseline in each triangulation cell based on the observation data of each base station on the target satellite; wherein, the baseline is the line connecting the master base station and each slave base station in the triangulation cell. The baseline direction vector calculation unit is used to construct the direction vector of each baseline in each triangulation unit based on the position coordinates of each base station in each triangulation unit. The delay correction model construction unit is used to combine the ionospheric delay and direction vector of each baseline in each triangulation unit, and construct the ionospheric delay correction model of each triangulation unit for the target satellite through linear fitting.

[0063] In some embodiments of this application, the ionospheric delay calculation unit includes a base station delay calculation subunit and a baseline delay calculation subunit; The base station delay calculation subunit is used to calculate the ionospheric delay of each base station to the target satellite based on the observation frequency and observation wavelength of each base station in the multiple frequency bands, combined with the carrier phase observation value and integer ambiguity of the target satellite in the multiple frequency bands. The baseline delay calculation subunit is used to obtain the ionospheric delay of each baseline in each triangulation unit based on the master base station at the beginning and the slave base station at the end of each baseline in each triangulation unit, combined with the ionospheric delay of each base station to the target satellite.

[0064] In some embodiments of this application, the ionosphere model construction and solution module 230 includes a spatial gradient vector calculation unit and a spatial flatness calculation unit; The spatial gradient vector calculation unit is used to solve each ionospheric delay correction model to obtain the spatial gradient vector of each triangulation unit; wherein, the spatial gradient vector includes the spatial gradient along the meridian and the spatial gradient along the parallel. The spatial flatness calculation unit is used to calculate the ionospheric delay spatial flatness corresponding to each triangulation unit based on the spatial gradient vector of all triangulation units.

[0065] In some embodiments of this application, the base station ambiguity optimization module 240 includes a candidate ambiguity generation unit, a candidate flatness calculation unit, and an optimized ambiguity determination unit; The alternative ambiguity generation unit is used to generate multiple alternative ambiguities based on the initial ambiguity of the target satellite and according to a preset number of error weeks. The alternative flatness calculation unit is used to solve the ionospheric delay correction model corresponding to each anomalous triangular mesh unit according to the multiple alternative ambiguities, and obtain multiple alternative ionospheric delay space flatness corresponding to each anomalous triangular mesh unit; wherein, the anomalous triangular mesh unit is a triangular mesh unit whose ionospheric delay space flatness is not less than a preset anomalous threshold. The optimized ambiguity determination unit is used to take the candidate ambiguity corresponding to the candidate ionospheric delay space flatness that meets the preset optimization conditions in each abnormal triangulation unit as the optimized ambiguity of the abnormal triangulation unit; wherein, the preset optimization conditions are less than the preset abnormal threshold and the smallest value among all candidate ionospheric delay space flatnesses in the abnormal triangulation unit.

[0066] In some embodiments of this application, a base station ambiguity determination module is also included; the base station ambiguity determination module is used to fix the integer ambiguity of each base station for the target satellite in a plurality of triangular mesh units in which the ionospheric delay spatial flatness is less than the preset anomaly threshold to the corresponding ambiguity true value.

[0067] This application first acquires observation data of the target satellite from each base station within the area to be detected. Then, it repeatedly divides the base stations into multiple triangular mesh units using triangulation. Next, it constructs and solves the ionospheric delay correction model for each triangular mesh unit to obtain the ionospheric delay spatial smoothness of each unit through linear fitting. Then, based on the initial ambiguity of the target satellite, it performs ambiguity optimization on triangular mesh units with ionospheric delay spatial smoothness not less than an anomaly threshold, determining the corresponding ambiguity ground truth. By dividing the base stations into triangular mesh units and constructing the ionospheric delay correction model with these units as the main body, it can characterize the spatial relationship between base stations based on the triangular mesh units. This allows the constructed ionospheric delay correction model to characterize the spatial distribution pattern of the ionosphere, thus enabling the reasonable use of ionospheric influence to fix base station ambiguities and improve the accuracy of base station ambiguity fixing. Simultaneously, by optimizing triangular mesh units whose ionospheric delay spatial smoothness does not meet the condition based on the initial ambiguity of the target satellite, it can further utilize ionospheric influence to correct the base station ambiguity optimization, improving the accuracy of the obtained optimized ambiguity and thus improving the accuracy of ambiguity fixing through ambiguity optimization.

[0068] It should be understood that the apparatus provided in this application is corresponding to the aforementioned method. The ambiguity fixing and optimization apparatus considering the ionosphere provided in this application can implement the ambiguity fixing and optimization method considering the ionosphere provided in any embodiment of this application.

[0069] Adaptively, embodiments of this application also provide a computer device and a computer-readable storage medium.

[0070] The computer device includes: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor; The processor, when executing the computer program, implements an ambiguity fixation optimization method considering the ionosphere, as described in this application.

[0071] The computer-readable storage medium stores multiple instructions adapted for loading by a processor to execute an ionospheric ambiguity fixation optimization method of this application.

[0072] The above description represents some embodiments of this application, providing a further detailed explanation of the purpose, technical solution, and beneficial effects of this application. It should be understood that the above-described embodiments of this application should not be construed as limiting this application. In particular, any changes, modifications, equivalent substitutions, and variations made by those skilled in the art within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for fixed optimization of ambiguity considering the ionosphere, characterized in that, include: Acquire observation data of the target satellite from each base station within the area to be detected; wherein, the observation data includes carrier phase observations and integer ambiguities of the target satellite under multiple preset frequency bands; Based on triangulation, all base stations are repeatedly divided to obtain multiple triangular network units. Based on the observation data of each base station on the target satellite, an ionospheric delay correction model for each triangular mesh unit is constructed by linear fitting, and each ionospheric delay correction model is solved to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit. Based on the initial ambiguity of the target satellite, ambiguity optimization is performed on several triangulation units with ionospheric delay spatial flatness not less than a preset anomaly threshold to obtain several optimized ambiguities, and the several optimized ambiguities are fixed as the true ambiguity values ​​of each base station in the corresponding triangulation unit for the target satellite.

2. The ambiguity fixation optimization method considering the ionosphere according to claim 1, characterized in that, The acquisition of observation data of the target satellite from each base station within the area to be detected specifically includes: Acquire initial observation data of the target satellite from each base station within the area to be detected in the multiple frequency bands; wherein, the initial observation data includes carrier phase observation values ​​of the target satellite in the multiple frequency bands; Based on the initial observation data of each base station, and using a preset integer ambiguity fixing method, the integer ambiguity of each base station for the target satellite in multiple frequency bands is calculated. Combining the initial observation data and integer ambiguity of each base station, the observation data of each base station for the target satellite is obtained.

3. The ambiguity fixation optimization method considering the ionosphere according to claim 1, characterized in that, The step of constructing an ionospheric delay correction model for the target satellite for each triangular mesh unit through linear fitting based on the observation data of each base station includes: Based on the observation data of each base station on the target satellite, the ionospheric delay of each baseline in each triangulation cell is calculated; wherein, the baseline is the connection between the master base station and each slave base station in the triangulation cell. Based on the location coordinates of each base station within each triangulation unit, construct the direction vector of each baseline within each triangulation unit; By combining the ionospheric delay and direction vector of each baseline within each triangulation cell, an ionospheric delay correction model for the target satellite is constructed for each triangulation cell through linear fitting.

4. The ambiguity fixation optimization method considering the ionosphere according to claim 3, characterized in that, The step of calculating the ionospheric delay of each baseline within each triangulation unit based on the observation data of each base station on the target satellite specifically includes: Based on the observation frequency and observation wavelength of each base station in the multiple frequency bands, and combined with the carrier phase observation value and integer ambiguity of the target satellite in the multiple frequency bands, the ionospheric delay of each base station to the target satellite is calculated. Based on the primary base station at the beginning and the secondary base station at the end of each baseline within each triangulation unit, and combined with the ionospheric delay of each base station relative to the target satellite, the ionospheric delay of each baseline within each triangulation unit is obtained.

5. The ambiguity fixation optimization method considering the ionosphere according to claim 1, characterized in that, The step of solving each ionospheric delay correction model to determine the ionospheric delay space flatness corresponding to each triangular mesh element specifically includes: Each ionospheric delay correction model is solved separately to obtain the spatial gradient vector of each triangular mesh unit; wherein, the spatial gradient vector includes the spatial gradient along the meridian and the spatial gradient along the parallel; Calculate the ionospheric delay spatial flatness corresponding to each triangulation cell based on the spatial gradient vectors of all triangulation cells.

6. The ambiguity fixation optimization method considering the ionosphere according to claim 1, characterized in that, The step involves optimizing the ambiguity of several triangular mesh units with ionospheric delay spatial flatness not less than a preset anomaly threshold, based on the initial ambiguity of the target satellite, to obtain several corresponding optimized ambiguities. Specifically, this includes: Based on the initial ambiguity of the target satellite, multiple alternative ambiguities are generated according to a preset error cycle. Based on the multiple candidate ambiguities, the ionospheric delay correction model corresponding to each anomalous triangular mesh unit is calculated respectively to obtain multiple candidate ionospheric delay spatial flatness corresponding to each anomalous triangular mesh unit; wherein, the anomalous triangular mesh unit is a triangular mesh unit whose ionospheric delay spatial flatness is not less than a preset anomalous threshold. The candidate ambiguity corresponding to the candidate ionospheric delay space flatness that meets the preset optimization conditions in each anomalous triangulation cell is taken as the optimized ambiguity of the anomalous triangulation cell; wherein, the preset optimization conditions are less than the preset anomalous threshold and have the smallest value among all candidate ionospheric delay space flatnesses in the anomalous triangulation cell.

7. The ambiguity fixation optimization method considering the ionosphere according to claim 1, characterized in that, Also includes: The integer ambiguity of each base station for the target satellite within a number of triangular mesh units where the ionospheric delay spatial flatness is less than the preset anomaly threshold is fixed as the corresponding ambiguity true value.

8. A device for ambiguity fixation optimization considering the ionosphere, characterized in that, It includes a base station observation data acquisition module, a triangulation unit division module, an ionospheric model construction and solution module, and a base station ambiguity optimization module; The base station observation data acquisition module is used to acquire observation data of the target satellite from each base station in the area to be detected; wherein, the observation data includes carrier phase observation values ​​and integer ambiguity of the target satellite under multiple preset frequency bands; The triangulation unit division module is used to repeatedly divide all base stations based on triangulation to obtain multiple triangulation units. The ionospheric model construction and solution module is used to construct an ionospheric delay correction model for each triangular mesh unit of the target satellite based on the observation data of each base station on the target satellite through linear fitting, and to solve each ionospheric delay correction model to determine the ionospheric delay spatial flatness corresponding to each triangular mesh unit. The base station ambiguity optimization module is used to perform ambiguity optimization on a number of triangulation units with ionospheric delay spatial flatness not less than a preset anomaly threshold according to the initial ambiguity of the target satellite, to obtain a number of optimized ambiguities, and to fix the number of optimized ambiguities as the true ambiguity values ​​of each base station for the target satellite in the corresponding triangulation unit.

9. A computer device, characterized in that, include: processor; Memory; A computer program stored in the memory and configured to be executed by the processor; When the processor executes the computer program, it implements a fixed ambiguity optimization method considering the ionosphere as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a plurality of instructions adapted for loading by a processor to execute the ambiguity fixing optimization method considering the ionosphere as described in any one of claims 1 to 7.

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