Beidou satellite ambiguity evaluation method, system, device, medium and product

Abstract

This invention discloses a method, system, device, medium, and product for evaluating ambiguity of BeiDou satellites. The method includes: receiving carrier observation data and observation conditions for each satellite transmitted from several BeiDou satellites to a base station; calculating integer ambiguity based on the carrier observation data; calculating first ionospheric delay information based on the carrier observation data, integer ambiguity, and preset ionospheric parameters; inputting the first ionospheric delay information and the observation conditions for each satellite into a preset ionospheric mapping model to obtain second ionospheric delay information for the base station; determining the residual error of each BeiDou satellite based on the second ionospheric delay information and each first ionospheric delay information; determining the allowable fluctuation range based on each residual error; and evaluating the integer ambiguity based on each allowable fluctuation range. This application can accurately identify whether the integer ambiguity fixation is correct under complex ionospheric environments and variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning results.

Description

Technical Field

[0001] This invention relates to the field of satellite navigation technology, and in particular to methods, systems, equipment, media and products for ambiguity assessment of BeiDou satellites. Background Technology

[0002] With the widespread application of the BeiDou Navigation Satellite System in fields such as precision surveying, deformation monitoring, and intelligent transportation, high-precision positioning technology based on carrier phase observation has placed higher demands on positioning reliability. In the BeiDou high-precision positioning process, the correct fixing of integer ambiguities is a prerequisite for achieving centimeter-level or even millimeter-level positioning accuracy. If the ambiguity fixing is incorrect, it will directly lead to a systematic deviation in the carrier phase calculation results, thereby affecting the accuracy of ionospheric delay calculation and the stability of the final positioning result. Therefore, after ambiguity fixing is completed, how to accurately and reliably detect the effectiveness of the integer ambiguity fixing results has become a key technical issue in ensuring the quality of BeiDou high-precision positioning. It is necessary to propose a method that can effectively determine the correctness of ambiguity fixing under single-station conditions.

[0003] In existing technologies, methods for detecting the effectiveness of integer ambiguity fixation mostly rely on the ambiguity parameters themselves or statistical residual information from the solution process. The detection basis primarily stems from the internal characteristics of ambiguity resolution, making the detection methods relatively singular and insufficient to comprehensively reflect the impact of ambiguity fixation errors on subsequent physical quantity calculations. Furthermore, although high-precision ionospheric delay information can be calculated from multi-frequency carrier observations when ambiguity is correctly fixed, and the ionospheric delays of different observation satellites at the same single station within the same observation epoch exhibit spatial correlation, existing methods typically do not fully utilize these ionospheric correlation features derived from ambiguity for joint detection. Moreover, when the ionospheric environment varies drastically with time and space, existing detection methods often employ fixed thresholds or simple statistical rules, which are difficult to adapt to the normal fluctuation range of residual errors after ionospheric delay mapping under different observation times, station locations, and satellite elevation and azimuth angles. This can easily lead to missed or misjudged ambiguity fixation errors, affecting the reliability and stability of BeiDou high-precision positioning. Summary of the Invention

[0004] This invention provides a method, system, equipment, medium, and product for evaluating ambiguity of BeiDou satellites. It can accurately identify whether integer ambiguity fixation is correct in complex ionospheric environments and under variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning results.

[0005] In a first aspect, embodiments of the present invention provide a method for evaluating the ambiguity of BeiDou satellites, including: The system receives several carrier observation data and satellite observation conditions transmitted from several BeiDou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each BeiDou satellite relative to the base station. The integer ambiguity corresponding to each BeiDou satellite is calculated based on the carrier observation data. The first ionospheric delay information of each BeiDou satellite is calculated based on the carrier observation data, the integer ambiguity, and the preset ionospheric parameters. The first ionospheric delay information and the satellite observation conditions are input into the preset ionospheric mapping model. The second ionospheric delay information of the base station is obtained by performing path normalization mapping on the first ionospheric delay information. The residual error of each BeiDou satellite after ionospheric delay mapping is determined based on the second ionospheric delay information and the first ionospheric delay information. Based on the residual errors, the allowable fluctuation range corresponding to each BeiDou satellite is determined, and the integer ambiguity corresponding to each BeiDou satellite is evaluated based on the allowable fluctuation range.

[0006] This invention improves the accuracy of BeiDou high-precision positioning by simultaneously processing ambiguity resolution and ionospheric delay analysis by combining observational information with actual spatial geometry. This provides a complete data foundation for subsequent multi-satellite joint analysis, enabling accurate identification of whether integer ambiguity fixation is correct under complex ionospheric environments and variable observation conditions. Furthermore, by deriving ionospheric delay directly from fixed integer ambiguity, a correspondence is established between ambiguity fixation results and changes in ionospheric physical quantities, further enhancing the accuracy of BeiDou high-precision positioning under complex ionospheric environments and variable observation conditions. Finally, by unifying ionospheric oblique path delays under different elevation and azimuth angles to the same reference direction for comparison, the influence of observational geometric differences on error discrimination is reduced. Accurately identifying the correctness of integer ambiguity fixation in complex ionospheric environments and under variable observation conditions improves the accuracy of BeiDou high-precision positioning. By explicitly quantifying the impact of ambiguity fixation errors on ionospheric consistency disruption as a residual error index, the detectability of abnormal ambiguity fixation results is enhanced, thus accurately identifying the correctness of integer ambiguity fixation in complex ionospheric environments and under variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning. Furthermore, by enabling the determination of ambiguity fixation correctness to adapt to the normal fluctuation characteristics of ionospheric delay residual errors under different observation times, station locations, and satellite observation conditions, misjudgments or omissions caused by fixed thresholds are avoided, thus accurately identifying the correctness of integer ambiguity fixation in complex ionospheric environments and under variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning.

[0007] Furthermore, the calculation of the integer ambiguity corresponding to each BeiDou satellite based on the carrier observation data includes: The carrier phase observation values ​​corresponding to several frequency bands, the carrier wavelength parameters corresponding to each frequency band, and the geometric distance parameters are input into the preset carrier phase observation equation to solve the carrier phase observation values ​​of each frequency band, thereby obtaining the floating-point ambiguity parameters of each Beidou satellite in each frequency band. The carrier observation data includes each carrier phase observation value and each carrier wavelength parameter, and the geometric distance parameter is the distance between each Beidou satellite and the base station. By applying an ambiguity fixing algorithm to each of the floating-point ambiguity parameters, integer constraints are applied to obtain the integer ambiguity of each BeiDou satellite in each frequency band.

[0008] This invention integrates multi-frequency carrier phase observations, corresponding wavelength parameters, and satellite-to-ground geometric distances into the carrier phase observation equation for joint calculation. This yields floating-point ambiguity parameters for each BeiDou satellite in each frequency band. Furthermore, an ambiguity fixing algorithm is used to constrain the floating-point ambiguity to obtain reliable integer ambiguity. This provides a stable and accurate ambiguity foundation for subsequent precise calculation of ionospheric delay based on carrier phase. Consequently, it accurately identifies whether the integer ambiguity fixing is correct under complex ionospheric environments and variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning.

[0009] Furthermore, the calculation of the first ionospheric delay information of each BeiDou satellite based on each of the carrier observation data, each of the integer ambiguities, and preset ionospheric parameters includes: Each integer ambiguity is summed with its corresponding carrier phase observation value to obtain the carrier phase combination quantity for each frequency band. The ionospheric equivalent distance of each Beidou satellite is determined based on the preset ionospheric parameters and the combination of each carrier phase. Based on the carrier frequency parameters corresponding to each frequency band, the equivalent ionospheric distance is linearly combined according to the squared difference relationship to obtain the first ionospheric delay information of each Beidou satellite.

[0010] This invention combines integer ambiguity with corresponding carrier phase observations to eliminate integer uncertainty in carrier phase observations. Furthermore, it utilizes the physical property that ionospheric delay is inversely proportional to the square at different frequencies to linearly combine multi-frequency carrier phase combinations, obtaining high-precision ionospheric delay information. This allows the ambiguity fixation result to be directly mapped to the ionospheric physical quantity space, which is beneficial for accurately identifying whether the integer ambiguity fixation is correct in complex ionospheric environments and under variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning.

[0011] Furthermore, the step of inputting each of the first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model, so as to obtain the second ionospheric delay information of the base station by performing path normalization mapping processing on each of the first ionospheric delay information, includes: The first ionospheric delay information and the observation conditions of each satellite are input into the preset ionospheric mapping model to determine the ionospheric path mapping relationship of each Beidou satellite based on the relative spatial position between each Beidou satellite and the base station. Based on the ionospheric path mapping relationships, the first ionospheric delay information is subjected to path normalization mapping processing to obtain the second ionospheric delay information of the base station.

[0012] This invention employs a unified path mapping and normalization process for ionospheric oblique path delay based on the relative spatial position between satellites and base stations. This transforms the ionospheric delay corresponding to different observed satellites into a comparable zenith direction delay representation, reducing the impact of differences in satellite elevation and azimuth angles on ionospheric delay. This provides a consistent and stable reference benchmark for subsequent residual error analysis, facilitating accurate identification of whether integer ambiguity fixation is correct under complex ionospheric environments and variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning.

[0013] Furthermore, the step of determining the allowable fluctuation range corresponding to each BeiDou satellite based on each of the residual errors, and then evaluating the integer ambiguity corresponding to each BeiDou satellite based on each of the allowable fluctuation ranges, includes: The acquired historical residual errors and corresponding historical satellite observation conditions are input into a preset time series prediction model. By learning the variation law of residual errors with observation time and satellite observation conditions, the allowable fluctuation range of each Beidou satellite under different satellite observation conditions can be obtained. The residual errors are compared with the allowable fluctuation range. If they exceed the range, the integer ambiguity of the corresponding BeiDou satellite is determined to be abnormal.

[0014] This invention utilizes a time series prediction model to characterize the normal fluctuation range of ionospheric delay mapping residual error under different observation times and satellite observation conditions. Based on this, it adaptively compares and judges the current residual error, avoiding misjudgment problems caused by using a fixed threshold. This enables accurate identification of whether the integer ambiguity is fixed correctly in complex ionospheric environments and under variable observation conditions, further improving the accuracy and reliability of BeiDou high-precision positioning results.

[0015] Furthermore, determining the residual error of each BeiDou satellite after ionospheric delay mapping based on the second ionospheric delay information and each of the first ionospheric delay information includes: performing differential calculations on the second ionospheric delay information and each of the first ionospheric delay information to obtain the residual error of each BeiDou satellite after ionospheric delay mapping.

[0016] This invention eliminates common ionospheric components and highlights single-satellite mapping error characteristics by differentiating the second ionospheric delay information after ionospheric path normalization with the first ionospheric delay information corresponding to each BeiDou satellite. This allows for a more sensitive reflection of whether integer ambiguity is fixed correctly in complex ionospheric environments and under variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning results.

[0017] Secondly, embodiments of the present invention provide a BeiDou satellite ambiguity evaluation system, the system comprising: an acquisition module, a mapping module, and an evaluation module; The acquisition module is used to receive several carrier observation data and satellite observation conditions transmitted from several Beidou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each Beidou satellite relative to the base station. The mapping module is used to calculate the integer ambiguity corresponding to each Beidou satellite based on each carrier observation data, calculate the first ionospheric delay information of each Beidou satellite based on each carrier observation data, each integer ambiguity and preset ionospheric parameters, input each first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model, so as to obtain the second ionospheric delay information of the base station by performing path normalization mapping processing on each first ionospheric delay information, and determine the residual error of each Beidou satellite after ionospheric delay mapping based on the second ionospheric delay information and each first ionospheric delay information. The evaluation module is used to determine the allowable fluctuation range corresponding to each Beidou satellite based on the residual errors, and to evaluate the integer ambiguity corresponding to each Beidou satellite based on the allowable fluctuation range.

[0018] This invention combines the integer ambiguity obtained from carrier observation with the residual error after ionospheric delay mapping, and adaptively determines the allowable fluctuation range based on satellite observation conditions. This enables a system-level evaluation of the integer ambiguity fixation results, thereby accurately identifying whether the integer ambiguity fixation is correct under complex ionospheric environments and variable observation conditions, and improving the accuracy and reliability of BeiDou high-precision positioning results.

[0019] Thirdly, embodiments of the present invention provide a terminal device, including: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction that causes the processor to perform the operation of the ambiguity evaluation method for BeiDou satellites as described in this application.

[0020] Fourthly, embodiments of the present invention provide a computer-readable storage medium comprising a stored computer program, wherein, when the computer program is executed, it controls the device or system where the computer-readable storage medium is located to execute the ambiguity evaluation method for BeiDou satellites as described in this application.

[0021] Based on the above-described method embodiments, another embodiment of the present invention provides a computer program product, including a computer program or instructions, which, when executed by a communication device, implements the ambiguity evaluation method for BeiDou satellites according to any embodiment of the present invention.

[0022] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0023] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 This is a flowchart illustrating one embodiment of the ambiguity assessment method for BeiDou satellites provided in this application; Figure 2 This is a flowchart illustrating steps S201 to S202 provided in this application; Figure 3 This is a flowchart illustrating steps S301 to S303 provided in this application; Figure 4 This is a schematic diagram of an embodiment of the ambiguity evaluation method for BeiDou satellites provided in this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0027] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0028] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0029] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0030] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0031] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0032] With the widespread application of the BeiDou Navigation Satellite System in fields such as precision surveying, deformation monitoring, and intelligent transportation, high-precision positioning based on carrier phase observation has placed higher demands on the reliability of positioning results. Among these, the correct fixation of integer ambiguity is a key prerequisite for achieving centimeter-level or even millimeter-level positioning accuracy. If the ambiguity is fixed incorrectly, it will cause systematic deviations in carrier phase calculation and ionospheric delay calculation, thereby affecting the stability of the positioning results. In existing technologies, methods for detecting the effectiveness of ambiguity fixation are mostly based on the ambiguity parameters themselves or statistical residual information in the solution process. The detection methods are relatively simple and cannot reflect the impact of ambiguity fixation errors on subsequent calculations of physical quantities such as ionospheric delay. At the same time, although high-precision ionospheric delay information can be obtained from multi-frequency carrier observations when the ambiguity is correctly fixed, and the ionospheric delays of different satellites within the same epoch of the same single station have a certain spatial correlation, existing methods usually do not make full use of these ionospheric correlation features derived from ambiguity for joint detection. Moreover, they often use fixed thresholds or simple statistical rules, which are difficult to adapt to the normal fluctuation range of residual errors after ionospheric delay mapping under different observation times, station locations, and satellite observation conditions. This can easily lead to missed detections or misjudgments of ambiguity fixation errors, affecting the reliability and stability of BeiDou high-precision positioning.

[0033] See Figure 1 In order to accurately identify whether the integer ambiguity fixation is correct in complex ionospheric environments and under variable observation conditions, so as to improve the accuracy of BeiDou high-precision positioning results, an embodiment of the present invention provides a BeiDou satellite ambiguity evaluation method, including steps S101 to S103. Step S101: Receive several carrier observation data and satellite observation conditions transmitted from several BeiDou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each BeiDou satellite relative to the base station. In some embodiments, based on a BeiDou receiver located at a base station, navigation signals transmitted by multiple BeiDou satellites are received within the same observation epoch, and the navigation signals are demodulated to obtain carrier phase observation data and pseudorange observation data of each BeiDou satellite in at least two frequency bands. The carrier phase observation data includes at least the carrier phase observation value and corresponding carrier wavelength parameter of the first frequency band, and the carrier phase observation value and corresponding carrier wavelength parameter of the second frequency band, for subsequent integer ambiguity estimation and ionospheric delay calculation. While acquiring the carrier observation data, based on the satellite orbit parameters and clock bias information in the BeiDou navigation message, and combined with the known spatial coordinate information of the base station, the geometric spatial relationship of each BeiDou satellite relative to the base station at the current observation epoch is calculated to determine the spatial positional relationship parameters between each BeiDou satellite and the base station. Further, based on the geometric spatial relationship parameters, the satellite elevation angle and azimuth angle of each BeiDou satellite relative to the base station are calculated and recorded as observation condition parameters for the corresponding BeiDou satellite. Thus, within the same observation epoch, an observation data set is formed that includes the following: for each participating BeiDou satellite, the corresponding multi-frequency carrier phase observation value, the carrier wavelength parameters for each frequency band, and the elevation angle and azimuth angle of the BeiDou satellite relative to the base station. This observation data set is used in subsequent steps to estimate and fix integer ambiguity, calculate ionospheric slant path delay, and evaluate ionospheric delay mapping residual error.

[0034] Through the above steps, multi-frequency carrier observation data of multiple BeiDou satellites and their corresponding space observation conditions are acquired simultaneously within the same observation epoch. This provides a complete and reliable data foundation for the accurate estimation and fixation of integer ambiguity, precise calculation of ionospheric delay, and effectiveness evaluation of ambiguity based on ionospheric mapping residues. This supports the accurate identification of whether the integer ambiguity fixation is correct under complex ionospheric environments and variable observation conditions, thereby improving the accuracy of BeiDou high-precision positioning results.

[0035] Step S102: Calculate the integer ambiguity corresponding to each BeiDou satellite based on the carrier observation data. Calculate the first ionospheric delay information of each BeiDou satellite based on the carrier observation data, the integer ambiguity, and preset ionospheric parameters. Input the first ionospheric delay information and the satellite observation conditions into a preset ionospheric mapping model. Obtain the second ionospheric delay information of the base station by performing path normalization mapping on the first ionospheric delay information. Determine the residual error of each BeiDou satellite after ionospheric delay mapping based on the second ionospheric delay information and the first ionospheric delay information. Please refer to Figure 2In some embodiments, the calculation of the integer ambiguity corresponding to each Beidou satellite based on the carrier observation data includes: steps S201 to S202; Step S201: Input the carrier phase observation values ​​corresponding to several frequency bands, the carrier wavelength parameters corresponding to each frequency band, and the geometric distance parameters into the preset carrier phase observation equation to solve the carrier phase observation values ​​of each frequency band and obtain the floating-point ambiguity parameters of each Beidou satellite in each frequency band. The carrier observation data includes each carrier phase observation value and each carrier wavelength parameter, and the geometric distance parameter is the distance between each Beidou satellite and the base station. In some embodiments, within the same observation epoch, the base station uses a BeiDou receiver to receive carrier phase observations from multiple BeiDou satellites in multiple frequency bands, and obtains the carrier wavelength parameters corresponding to each frequency band. Simultaneously, based on the BeiDou satellite ephemeris information and the base station's spatial location parameters, the geometric distance parameters between each BeiDou satellite and the base station are calculated. For any given BeiDou satellite, the carrier phase observation equation in the first frequency band is expressed as: ; in, The carrier phase observation values ​​for the first frequency band, The carrier wavelength parameters corresponding to the first frequency band. These are the geometric distance parameters between BeiDou satellites and base stations. This is an ionospheric delay correction term. For tropospheric delay correction term, Let be the ambiguity parameter corresponding to the first frequency band. Rearranging the above carrier phase observation equations, we obtain the formula for calculating the floating-point ambiguity parameter of the first frequency band as follows: By substituting the carrier phase observations, carrier wavelength parameters, and geometric distance parameters of the first frequency band into the above formula, the first floating-point ambiguity parameter of the BeiDou satellite in the first frequency band is obtained. Furthermore, for the second frequency band, the same solution method as the first frequency band is used, and its carrier phase observation equation is: ; in, These are the carrier phase observations for the second frequency band. The carrier wavelength parameters corresponding to the second frequency band. These are the geometric distance parameters between the BeiDou satellite and the base station. This is an ionospheric delay correction term. For tropospheric delay correction term, This refers to the ambiguity parameters corresponding to the second frequency band. And it is expressed by the formula: The second floating-point ambiguity parameter of the BeiDou satellite in the second frequency band is calculated. Following the above method, the carrier phase observations of each BeiDou satellite in each frequency band are processed to obtain the floating-point ambiguity parameters of each BeiDou satellite in each frequency band.

[0036] Step S202: The floating-point ambiguity parameters are subjected to integer constraint processing by the ambiguity fixing algorithm to obtain the integer ambiguity of each Beidou satellite in each frequency band.

[0037] In some embodiments, the floating-point ambiguity parameters of each BeiDou satellite in each frequency band obtained in step S201 are used to form an ambiguity vector, and an integer least squares problem is constructed with the objective of minimizing the error between floating-point ambiguity and integer ambiguity. Its mathematical expression is as follows: ,in, It is a vector composed of floating-point ambiguity parameters for each frequency band. For the corresponding integer ambiguity candidate vector, Let be the covariance matrix of the floating-point ambiguity parameters. By employing a fixed ambiguity algorithm to solve the aforementioned integer least squares problem, the integer solution that best matches the floating-point ambiguity parameters is determined, thereby obtaining the integer ambiguity of each BeiDou satellite in each frequency band. This step converts the floating-point ambiguity parameters into integer-form integer ambiguities, clearly quantifying the integer uncertainty in carrier phase observations and providing a reliable ambiguity foundation for subsequent high-precision ionospheric delay calculations based on multi-frequency carrier observations.

[0038] It should be noted that the method of using a fixed ambiguity algorithm to solve the above-mentioned integer least squares problem includes the following steps: Arranging the floating-point ambiguity parameters of each BeiDou satellite in each frequency band obtained in step S201 according to the frequency band and satellite order to form a floating-point ambiguity vector: Simultaneously, based on the statistical characteristics of observation noise obtained during carrier phase observation calculation, the covariance relationship between each floating-point ambiguity parameter is calculated, yielding the corresponding covariance matrix: Among them, the covariance matrix This is used to characterize the correlation between floating-point ambiguity parameters of different frequency bands and different satellites. To reduce the correlation between floating-point ambiguity parameters and improve integer search efficiency, an integer equivalent transformation is performed on the floating-point ambiguity vector and its covariance matrix. By decomposing the covariance matrix, an integer transformation matrix is ​​obtained, and based on this, a linear transformation is performed on the floating-point ambiguity vector to obtain the transformed ambiguity vector and covariance matrix: ; in, The transformation matrix is ​​an integer invertible transformation matrix, which significantly reduces the correlation between ambiguity components after transformation. Based on the decorrelated ambiguity vectors and covariance matrix, a search region is constructed in the integer space, and integer candidate solutions are enumerated and searched according to the least squares criterion. For any integer candidate vector... Calculate the corresponding objective function value: By using a layer-by-layer search, several integer candidate solutions with the smallest objective function values ​​are selected as candidate ambiguity fixation results. The objective function values ​​corresponding to all candidate integer solutions are compared, and the integer vector with the smallest objective function value is selected as the optimal integer solution. Subsequently, by inverse transformation of the integer transformation matrix, the optimal integer solution is transformed back to the original ambiguity space to obtain the integer ambiguity vector of each BeiDou satellite in each frequency band: The integer ambiguity vector is used as the final ambiguity fixation result for subsequent ionospheric slant path delay calculation based on multi-frequency carrier observations and ambiguity fixation reliability assessment. Through these steps, integer constraint solutions for floating-point ambiguity parameters are achieved, accurately fixing the integer uncertainty in carrier phase observations to integer values, thereby improving the accuracy and stability of subsequent distance calculations and ionospheric delay estimations.

[0039] Please refer to Figure 3 In some embodiments, the step of calculating the first ionospheric delay information of each Beidou satellite based on each carrier observation data, each integer ambiguity and preset ionospheric parameters includes: steps S301 to S303; Step S301: Add each integer ambiguity to the corresponding carrier phase observation value to obtain the carrier phase combination quantity for each frequency band. In some embodiments, based on the BeiDou satellite data received by base station A at the current epoch... After fixing the integer ambiguity, the integer ambiguity corresponding to each frequency band is summed with the carrier phase observation value to eliminate integer discontinuities in the carrier phase observation, thus obtaining a continuous carrier phase combination. Taking the B1 and B2 frequency bands (i.e., the first and second frequency bands) as examples, their carrier phase combination values ​​are obtained according to the following formulas: ; in, , For base station A to monitor BeiDou satellites The carrier phase combination quantity in the B1 and B2 frequency bands, in units of length; , These are the carrier wavelengths corresponding to the B1 and B2 frequency bands, respectively. , For each of the base station A and the satellite Integer ambiguity in the B1 and B2 frequency bands; , For each of the base station A and the satellite The carrier phase observations in the B1 and B2 bands are expressed in cycles. Through the above processing, the carrier phase observations are transformed from periodic quantities into continuous distance quantities, providing a foundation for accurate calculation of subsequent ionospheric delay.

[0040] Step S302: Determine the ionospheric equivalent distance of each Beidou satellite based on the preset ionospheric parameters and the combination of each carrier phase; In some embodiments, based on the physical characteristic that ionospheric delay exhibits an inverse square relationship across different carrier frequency bands, the carrier phase combination quantities obtained in step S301 for different frequency bands are used to compare the data between the base station A and the BeiDou satellite. The equivalent ionospheric distance between the two bands is calculated. Specifically, the carrier phase combination quantities in the B1 and B2 frequency bands are differentially processed to obtain the combination quantity related to the ionospheric delay height, and its calculation formula is as follows: Substituting the carrier phase combination quantity in step S301 into the above formula, it can be further expressed as: ; in, For base station A to monitor satellites The ionospheric equivalent distance is calculated by eliminating common terms such as satellite-to-ground geometric distance, clock bias, and tropospheric delay, which are essentially consistent across different frequency bands. It primarily reflects the differential effects of ionospheric delay across different frequency bands. Through these steps, carrier phase observation information is transformed into a distance quantity expression directly related to ionospheric delay.

[0041] Step S303: Based on the carrier frequency parameters corresponding to each frequency band, the equivalent ionospheric distance is linearly combined according to the square difference relationship to obtain the first ionospheric delay information of each Beidou satellite.

[0042] In some embodiments, based on the characteristic that ionospheric delay is inversely proportional to the square of the carrier frequency, the ionospheric equivalent distance obtained in step S302 is used, and combined with the carrier frequency parameters corresponding to the B1 and B2 frequency bands, the ionospheric equivalent distance is weighted and linearly combined to obtain the distance between the base station A and the satellite. The first ionospheric delay information, namely the ionospheric slant path delay. Its calculation formula is as follows: ; in, For base station A to monitor BeiDou satellites The first ionospheric delay information, namely the ionospheric slant path delay; These represent the carrier frequencies corresponding to frequency bands B1 and B2, respectively; the meanings of the other symbols are as described above. Through the above weighted combination processing of squared differences, the ionospheric influence terms in the carrier phase of different frequency bands are separated and amplified, achieving millimeter-level accuracy estimation of the ionospheric slant delay of each observation satellite. This provides reliable input data for subsequent ionospheric mapping, residual error analysis, and ambiguity fixation accuracy verification.

[0043] In some embodiments, the step of inputting each of the first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model to obtain the second ionospheric delay information of the base station by performing path normalization mapping processing on each of the first ionospheric delay information includes: inputting each of the first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model to determine the ionospheric path mapping relationship corresponding to each BeiDou satellite based on the relative spatial position between each BeiDou satellite and the base station; and performing path normalization mapping processing on each of the first ionospheric delay information based on each of the ionospheric path mapping relationships to obtain the second ionospheric delay information of the base station.

[0044] In some embodiments, the first ionospheric delay information and the observation conditions of each satellite are input into a preset ionospheric mapping model to determine the ionospheric path mapping relationship corresponding to each BeiDou satellite based on the relative spatial position between each BeiDou satellite and the base station. Specifically, after calculating the first ionospheric delay information of each BeiDou satellite, the ionospheric oblique path delay information obtained by the reference station A for each observation satellite within the same epoch is used as the input quantity. At the same time, the spatial geometric observation conditions of each BeiDou satellite relative to the reference station A are combined to construct the ionospheric path mapping relationship. Among them, the observation conditions of each BeiDou satellite include the spatial position information of the reference station A and the spatial pointing information of each observation satellite in the current epoch, specifically including: the latitude of the reference station A. ,longitude and elevation Beidou satellite Azimuth relative to base station A With elevation angle Based on this, and using the single-layer ionosphere hypothesis model, a mapping relationship between ionospheric oblique path delay and zenith-direction ionospheric delay is constructed, and the ionospheric path mapping relationship for each observation satellite is expressed as an ionospheric delay mapping function. For multiple observation satellites at the current epoch of reference station A, their ionospheric path mapping relationship can be uniformly represented in the following matrix form: ; in, For base station A and Beidou satellite The first ionospheric delay information between them, namely the ionospheric slant path delay; The ionospheric delay of reference station A in the zenith direction; This is an ionospheric path mapping function constructed based on a single-layer ionospheric model, used to characterize the geometric mapping relationship between the oblique path and the zenith path. Through the above processing, the ionospheric path mapping relationship corresponding to each BeiDou satellite was determined, providing a foundation for the subsequent unified normalization of ionospheric delay.

[0045] In some embodiments, the first ionospheric delay information of each base station is subjected to path normalization mapping based on the ionospheric path mapping relationships to obtain the second ionospheric delay information of the base station. Specifically, based on the ionospheric path mapping relationships determined above, the first ionospheric delay information corresponding to each observed satellite of the base station A at the current epoch is subjected to path normalization mapping, and the slant path ionospheric delay is uniformly mapped to the zenith direction of the base station to obtain the second ionospheric delay information of the base station. Specifically, the ionospheric zenith direction delay of the base station A is solved based on the path mapping relationship in the least squares sense. And this zenith direction delay is used as the base station's second ionospheric delay information. After obtaining... Next, the mapping residual error of the ionospheric delay of each BeiDou satellite is further calculated, and the calculation formula is as follows: ; in, For base station A to monitor BeiDou satellites The residual error after ionospheric delay mapping is used to characterize the fit of the ionospheric mapping model to the actual slant path delay. Furthermore, statistical analysis is performed on the mapping residual errors of all observed satellites participating in the calculation within the current epoch to obtain the posterior variance after ionospheric delay mapping, calculated using the following formula: ; in, The a posteriori variance of the residual error of the ionospheric delay mapping at the current epoch of reference station A; The number of observation satellites participating in the ionospheric mapping calculation is specified. Through the above path normalization mapping process, the ionospheric oblique path delay of multiple BeiDou satellites is uniformly converted into the ionospheric delay expression form of the base station zenith direction, thereby obtaining stable and highly comparable base station second ionospheric delay information, providing reliable input for subsequent residual error modeling and ambiguity fixation correctness judgment.

[0046] In some embodiments, determining the residual error of each BeiDou satellite after ionospheric delay mapping based on the second ionospheric delay information and each of the first ionospheric delay information includes: performing differential calculations on the second ionospheric delay information and each of the first ionospheric delay information to obtain the residual error of each BeiDou satellite after ionospheric delay mapping.

[0047] In some embodiments, the second ionospheric delay information and each of the first ionospheric delay information are differentially calculated to obtain the residual error of each BeiDou satellite after ionospheric delay mapping. Specifically, after determining the second ionospheric delay information of reference station A, the second ionospheric delay information and the first ionospheric delay information corresponding to each BeiDou satellite are differentially processed on a satellite-by-satellite basis to obtain the residual error of each BeiDou satellite after ionospheric delay mapping. The second ionospheric delay information is the ionospheric delay of reference station A in the zenith direction. The first ionospheric delay information is the ionospheric slant path delay between base station A and each BeiDou satellite. Specifically, for any BeiDou satellite First, based on the ionospheric path mapping relationship corresponding to the satellite, the second ionospheric delay information is mapped to the oblique path direction corresponding to the satellite to obtain the mapped ionospheric delay of the satellite. The calculation expression is as follows: Based on this, the ionospheric delay obtained from the above mapping is differentially calculated with the first ionospheric delay information corresponding to the satellite to obtain the residual error of the BeiDou satellite after ionospheric delay mapping. The calculation formula is as follows: ; in, For base station A to monitor BeiDou satellites The residual error after ionospheric delay mapping; For base station A and Beidou satellite The ionospheric slant path delay between them, i.e., the first ionospheric delay information; The ionospheric delay of reference station A in the zenith direction is the second ionospheric delay information. These are the latitude, longitude, and elevation information of base station A; Beidou satellites The azimuth and elevation angles relative to base station A; This is the ionospheric delay mapping function, used to characterize the geometric mapping relationship between the ionospheric oblique path and the zenith path. By performing the above difference calculation on all observed BeiDou satellites within the current epoch, a set of residual errors after ionospheric delay mapping is obtained. This set is used to characterize the consistency of the ionospheric mapping model's fit to the ionospheric delay of each observed satellite, and to provide basic data support for subsequent statistical analysis of residual errors and determination of the correctness of ambiguity fixation.

[0048] Through the above steps, the ionospheric slant path delay obtained from multi-frequency carrier observation is uniformly mapped to the zenith direction of the base station. The residual error of the ionospheric delay mapping is obtained by the difference between the slant path and the mapping result. This residual error can directly reflect the impact of the ambiguity fixation result on the physical consistency of the ionosphere. Thus, in complex ionospheric environments and under variable observation conditions, it is possible to accurately identify whether the integer ambiguity fixation is correct, thereby improving the accuracy and reliability of BeiDou high-precision positioning results.

[0049] Step S103: Determine the allowable fluctuation range corresponding to each Beidou satellite based on the residual errors, and evaluate the integer ambiguity corresponding to each Beidou satellite based on the allowable fluctuation range.

[0050] In some embodiments, determining the allowable fluctuation range corresponding to each BeiDou satellite based on the residual errors, and evaluating the integer ambiguity corresponding to each BeiDou satellite based on the allowable fluctuation range, includes: inputting the acquired historical residual errors and corresponding historical satellite observation conditions into a preset time series prediction model, so as to learn the variation law of residual errors with observation time and satellite observation conditions to obtain the allowable fluctuation range of each BeiDou satellite under different satellite observation conditions; comparing each residual error with the allowable fluctuation range, and if it exceeds the allowable fluctuation range, determining that the integer ambiguity of the corresponding BeiDou satellite is fixed abnormally.

[0051] In some embodiments, the acquired historical residual errors and corresponding historical satellite observation conditions are input into a preset time series prediction model to learn the variation law of residual errors with observation time and satellite observation conditions, thereby obtaining the allowable fluctuation range of each BeiDou satellite under different satellite observation conditions. Specifically, based on historical observation data, the residual errors after ionospheric delay mapping corresponding to each BeiDou satellite at multiple epochs are obtained, along with satellite observation condition information corresponding one-to-one with the residual errors. The satellite observation conditions include the spatial location of the reference station, the observation time, and the elevation and azimuth angles of the BeiDou satellite relative to the reference station. The historical residual errors and corresponding historical satellite observation conditions are arranged in chronological order to form a residual error time series sample, and the time series sample is input into the preset time series prediction model for training. The time series prediction model is a neural network model based on a long short-term memory network. Through the long short-term memory network model, the temporal characteristics of residual errors changing with time and satellite observation conditions are learned, obtaining the statistical fluctuation characteristics of residual errors under different observation conditions, thereby forming a residual error test threshold model, the mathematical expression of which is: ; in, This refers to the allowable fluctuation range of residual error under given observation conditions. These are the latitude, longitude, and elevation information of base station A; The epoch of the observation time; Beidou satellites The residual error test threshold model is used to characterize the reasonable fluctuation range of residual error after ionospheric delay mapping under different times and different satellite spatial geometry conditions, relative to the azimuth and elevation angles of reference station A.

[0052] In some embodiments, each residual error is compared with the allowable fluctuation range. If the range is exceeded, the integer ambiguity fixation of the corresponding BeiDou satellite is determined to be abnormal. Specifically, for the residual errors after ionospheric delay mapping of each BeiDou satellite obtained at the current epoch, they are compared with the allowable fluctuation range output by the residual error verification threshold model. Simultaneously, the statistical characteristics of the residual errors are considered to comprehensively determine the integer ambiguity fixation result. Specifically, for any BeiDou satellite... The integer ambiguity fixing result of the Beidou satellite is considered valid when the following conditions are met: ; in, For Beidou satellites The residual error after ionospheric delay mapping; This refers to the allowable fluctuation range of residual error obtained based on historical data and a long short-term memory network model. This is the a posteriori variance of the residual errors of all observed satellites at the current epoch; The carrier wavelength corresponds to the frequency band. If any of the above conditions are not met, the integer ambiguity fixing result corresponding to the BeiDou satellite is determined to be abnormal, and the ambiguity result of the satellite is marked as unreliable or a re-fixing process is triggered to avoid the abnormal ambiguity affecting the subsequent ionospheric parameter estimation and positioning accuracy.

[0053] Through the above steps, by utilizing the temporal correlation characteristics between historical residual errors and satellite observation conditions, a reasonable fluctuation range of residual errors under different time and spatial geometric conditions is adaptively constructed. Based on this, a multi-condition consistency test is performed on the current epoch integer ambiguity fixing result. This allows for accurate identification of whether the integer ambiguity fixing is correct under complex ionospheric environments and variable observation conditions, avoiding the introduction of positioning errors by abnormal ambiguities and improving the stability and accuracy of BeiDou high-precision positioning.

[0054] like Figure 4 As shown, based on the above method embodiments, corresponding apparatus embodiments are provided; An embodiment of the present invention provides a schematic diagram of the structure of a BeiDou satellite ambiguity evaluation system, including: an acquisition module 100, a mapping module 200, and an evaluation module 300; The acquisition module 100 is used to receive several carrier observation data and satellite observation conditions transmitted from several Beidou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each Beidou satellite relative to the base station. The mapping module 200 is used to calculate the integer ambiguity corresponding to each Beidou satellite based on each carrier observation data, calculate the first ionospheric delay information of each Beidou satellite based on each carrier observation data, each integer ambiguity and preset ionospheric parameters, input each first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model, so as to obtain the second ionospheric delay information of the base station by performing path normalization mapping on each first ionospheric delay information, and determine the residual error of each Beidou satellite after ionospheric delay mapping based on the second ionospheric delay information and each first ionospheric delay information. The evaluation module 300 is used to determine the allowable fluctuation range corresponding to each Beidou satellite based on the residual errors, and to evaluate the integer ambiguity corresponding to each Beidou satellite based on the allowable fluctuation range.

[0055] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the ambiguity evaluation method for BeiDou satellites provided by any of the above-described method embodiments of the present invention. For a more detailed workflow and principle of this system, please refer to the relevant descriptions of the above methods.

[0056] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0057] Based on the above embodiments of the ambiguity assessment method for BeiDou satellites, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the ambiguity assessment method for BeiDou satellites according to any embodiment of the present invention.

[0058] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0059] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0060] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0061] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the ambiguity evaluation method for BeiDou satellites as described in any of the above-described method embodiments of the present invention.

[0062] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0063] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for ambiguity evaluation of a Beidou satellite, characterized in that, include: The system receives several carrier observation data and satellite observation conditions transmitted from several BeiDou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each BeiDou satellite relative to the base station. The integer ambiguity corresponding to each BeiDou satellite is calculated based on the carrier observation data. The first ionospheric delay information of each BeiDou satellite is calculated based on the carrier observation data, the integer ambiguity, and the preset ionospheric parameters. The first ionospheric delay information and the satellite observation conditions are input into the preset ionospheric mapping model. The second ionospheric delay information of the base station is obtained by performing path normalization mapping on the first ionospheric delay information. The residual error of each BeiDou satellite after ionospheric delay mapping is determined based on the second ionospheric delay information and the first ionospheric delay information. Based on the residual errors, the allowable fluctuation range corresponding to each BeiDou satellite is determined, and the integer ambiguity corresponding to each BeiDou satellite is evaluated based on the allowable fluctuation range.

2. The ambiguity evaluation method of the Beidou satellite according to claim 1, characterized in that, The calculation of the integer ambiguity corresponding to each BeiDou satellite based on the carrier observation data includes: The carrier phase observation values ​​corresponding to several frequency bands, the carrier wavelength parameters corresponding to each frequency band, and the geometric distance parameters are input into the preset carrier phase observation equation to solve the carrier phase observation values ​​of each frequency band, thereby obtaining the floating-point ambiguity parameters of each Beidou satellite in each frequency band. The carrier observation data includes each carrier phase observation value and each carrier wavelength parameter, and the geometric distance parameter is the distance between each Beidou satellite and the base station. By applying an ambiguity fixing algorithm to each of the floating-point ambiguity parameters, integer constraints are applied to obtain the integer ambiguity of each BeiDou satellite in each frequency band.

3. The method of ambiguity evaluation of a Beidou satellite according to claim 2, wherein, The calculation of the first ionospheric delay information of each BeiDou satellite based on the carrier observation data, the integer ambiguity, and the preset ionospheric parameters includes: Each integer ambiguity is summed with its corresponding carrier phase observation value to obtain the carrier phase combination quantity for each frequency band. The ionospheric equivalent distance of each BeiDou satellite is determined based on the preset ionospheric parameters and the combination of each carrier phase. Based on the carrier frequency parameters corresponding to each frequency band, the equivalent ionospheric distance is linearly combined according to the squared difference relationship to obtain the first ionospheric delay information of each Beidou satellite.

4. The ambiguity evaluation method of the Beidou satellite according to claim 1, characterized in that, The step of inputting each of the first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model, so as to obtain the second ionospheric delay information of the base station by performing path normalization mapping processing on each of the first ionospheric delay information, includes: The first ionospheric delay information and the observation conditions of each satellite are input into the preset ionospheric mapping model to determine the ionospheric path mapping relationship of each Beidou satellite based on the relative spatial position between each Beidou satellite and the base station. Based on the ionospheric path mapping relationships, the first ionospheric delay information is subjected to path normalization mapping processing to obtain the second ionospheric delay information of the base station.

5. The ambiguity assessment method for BeiDou satellites as described in claim 1, characterized in that, The step of determining the allowable fluctuation range for each BeiDou satellite based on the residual errors, and then evaluating the integer ambiguity for each BeiDou satellite based on the allowable fluctuation ranges, includes: The acquired historical residual errors and corresponding historical satellite observation conditions are input into a preset time series prediction model. By learning the variation law of residual errors with observation time and satellite observation conditions, the allowable fluctuation range of each Beidou satellite under different satellite observation conditions can be obtained. The residual errors are compared with the allowable fluctuation range. If they exceed the range, the integer ambiguity of the corresponding BeiDou satellite is determined to be abnormal.

6. The ambiguity assessment method for BeiDou satellites as described in claim 1, characterized in that, The step of determining the residual error of each BeiDou satellite after ionospheric delay mapping based on the second ionospheric delay information and each of the first ionospheric delay information includes: performing differential calculations on the second ionospheric delay information and each of the first ionospheric delay information to obtain the residual error of each BeiDou satellite after ionospheric delay mapping.

7. A BeiDou satellite ambiguity assessment system, characterized in that, The system includes: an acquisition module, a mapping module, and an evaluation module; The acquisition module is used to receive several carrier observation data and satellite observation conditions transmitted from several Beidou satellites to the base station. The satellite observation conditions include the spatial position of the base station and the elevation angle and azimuth angle of each Beidou satellite relative to the base station. The mapping module is used to calculate the integer ambiguity corresponding to each Beidou satellite based on each carrier observation data, calculate the first ionospheric delay information of each Beidou satellite based on each carrier observation data, each integer ambiguity and preset ionospheric parameters, input each first ionospheric delay information and each satellite observation condition into a preset ionospheric mapping model, so as to obtain the second ionospheric delay information of the base station by performing path normalization mapping processing on each first ionospheric delay information, and determine the residual error of each Beidou satellite after ionospheric delay mapping based on the second ionospheric delay information and each first ionospheric delay information. The evaluation module is used to determine the allowable fluctuation range corresponding to each Beidou satellite based on the residual errors, and to evaluate the integer ambiguity corresponding to each Beidou satellite based on the allowable fluctuation range.

8. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the ambiguity evaluation method for BeiDou satellites as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform the ambiguity evaluation method for BeiDou satellites as described in any one of claims 1-6.

10. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by the communication device, the ambiguity evaluation method for BeiDou satellites as described in any one of claims 1 to 6 is implemented.

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