Whole cycle ambiguity test method, device, medium and equipment
Through the judgment of the difference between multiple full-week ambiguity solutions and the baseline vector fixed solution, the problem of poor reliability of full-week ambiguity solutions caused by threshold sensitivity in the prior art is solved, and a higher stability and reliability of full-week ambiguity solutions are achieved.
Patent Information
- Application Number
- CN202510692426.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-27
- Publication Date
- 2025-08-08
AI Technical Summary
The existing full-week ambiguity test methods have threshold sensitivity problems, which leads to poor reliability of the full-week ambiguity solution results, which may lead to partial effective solutions being erroneously eliminated or increased risk of inclusion.
By determining multiple double-difference observation equations, performing multiple full-week ambiguity solutions, comparing the difference between the maximum and minimum values of the fixed solution of the baseline vector with the preset threshold, and determining the stability of the full-week ambiguity solution. If the stability is high enough, the solution result will be accepted.
The reliability of the ambiguity test in the whole week is improved, the problem of inclusion is weakened, the reliability of the baseline solution results is enhanced, and the fixed success rate of ambiguity in the whole week is improved.
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Figure CN120447003A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of satellite navigation and positioning technology, and in particular to an integer ambiguity detection method, device, medium and equipment. Background Art
[0002] Currently, correctly fixing integer ambiguities is a key issue in real-time, high-precision positioning for the Global Navigation Satellite System (GNSS), directly impacting the accuracy and convergence speed of GNSS high-precision positioning. Therefore, improving the reliability of integer ambiguity fixation has long been a hot topic in GNSS research.
[0003] In general, integer ambiguity fixation involves two main steps: integer ambiguity resolution and integer ambiguity verification. Integer ambiguity resolution typically uses the integer least squares (ILS) method to estimate integer parameters and obtain the optimal integer solution. Integer ambiguity verification verifies the optimal integer solution obtained by ILS to ensure that the resulting integer ambiguity solution is accurate and reliable.
[0004] In the prior art, the most commonly used integer ambiguity test method is the Ratio test, which calculates the quadratic ratio between the optimal integer solution and the suboptimal integer solution and compares it with a set threshold to determine whether to accept the current integer solution.
[0005] However, the Ratio test suffers from threshold sensitivity. When the threshold is set too high, some valid integer ambiguity solutions may be mistakenly rejected. When the threshold is set too low, the risk of false positives may increase, thus affecting the reliability of the solution. Therefore, the current integer ambiguity test method has poor reliability. Summary of the Invention
[0006] Based on this, it is necessary to provide a whole-cycle ambiguity verification method, device, medium and equipment to address the above technical problems.
[0007] The present invention adopts the following technical solutions:
[0008] The present invention provides an integer ambiguity detection method, comprising:
[0009] Determine multiple double-difference observation equations based on carrier phase observation values and pseudo-range observation values of the satellite received by the receiver;
[0010] According to multiple double-difference observation equations and different subsets of multiple double-difference observation equations, multiple integer ambiguity resolutions are performed to obtain multiple sets of integer ambiguities and their corresponding baseline vector fixed solutions;
[0011] If the difference between the maximum and minimum values in the multiple sets of baseline vector fixed solutions is less than or equal to the preset threshold, it is determined that the integer ambiguity parameters obtained by solving the multiple double-difference observation equations are fixed correctly.
[0012] Optionally, performing multiple integer ambiguity resolutions according to the multiple double-difference observation equations and different subsets of the multiple double-difference observation equations specifically includes:
[0013] Integer ambiguity resolution is performed based on multiple double-difference observation equations;
[0014] For each double-difference observation equation, the double-difference observation equation is eliminated, and the integer ambiguity is resolved based on the remaining double-difference observation equations.
[0015] Optionally, perform integer ambiguity resolution, specifically including:
[0016] Obtain floating-point solutions to ambiguities using any of the following methods: least squares, Kalman filtering, and graph optimization;
[0017] The integer ambiguity is solved using the integer least squares method based on the ambiguity floating point solution.
[0018] Optionally, the method further includes:
[0019] If the difference between the maximum and minimum values in multiple sets of baseline vectors is less than or equal to a preset threshold, the baseline vector fixed solution corresponding to the integer ambiguity obtained by solving multiple double-difference observation equations is output;
[0020] If the difference between the maximum and minimum values in multiple groups of baseline vectors is greater than a preset threshold, the baseline vector floating-point solution obtained by solving multiple double-difference observation equations is output.
[0021] Optionally, the preset threshold is 0.015m.
[0022] The present invention provides an integer ambiguity checking device, comprising:
[0023] A construction module is used to determine a plurality of double-difference observation equations based on carrier phase observation values and pseudorange observation values of satellites received by a receiver;
[0024] A solution module is used to perform multiple integer ambiguity solutions based on multiple double-difference observation equations and different subsets of multiple double-difference observation equations, so as to obtain multiple sets of integer ambiguities and their corresponding baseline vector fixed solutions;
[0025] The verification module is used to determine that the integer ambiguity parameters obtained by solving multiple double-difference observation equations are fixed correctly if the difference between the maximum and minimum values in the multiple sets of baseline vector fixed solutions is less than or equal to a preset threshold.
[0026] The present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the integer ambiguity checking method described above is implemented.
[0027] The present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned integer ambiguity checking method when executing the program.
[0028] At least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects:
[0029] Based on the concept that more accurate integer ambiguity resolution leads to more stable integer ambiguity resolution, this present invention proposes determining multiple observation equations based on data acquired by a receiver. Multiple integer ambiguity resolutions are then performed based on the full set and multiple different subsets of these observation equations. The stability of the integer ambiguity resolution is then determined by comparing the difference between the maximum and minimum values of the baseline vector fixed solution in the multiple solution results with a preset threshold. If the integer ambiguity resolution is sufficiently stable, the corresponding integer ambiguity solution is accurate and effective, with high reliability, and can be accepted for subsequent applications. This present invention improves the reliability of the integer ambiguity verification method. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:
[0031] Figure 1 A flow chart of an integer ambiguity checking method provided by the present invention;
[0032] Figure 2 A schematic diagram of a specific implementation flow of an integer ambiguity detection method provided by the present invention;
[0033] Figure 3 A schematic diagram of an integer ambiguity detection device provided by the present invention;
[0034] Figure 4 A schematic diagram of a computer device for implementing the integer ambiguity checking method provided by the present invention. DETAILED DESCRIPTION
[0035] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0036] The technical solutions provided by various embodiments of the present invention are described in detail below with reference to the accompanying drawings.
[0037] Figure 1 The flowchart of the integer ambiguity detection method in the present invention specifically includes the following steps:
[0038] S101: Determine multiple double-difference observation equations based on carrier phase observation values and pseudorange observation values of satellites received by a receiver.
[0039] S102: Perform multiple integer ambiguity resolutions based on the multiple double-difference observation equations and different subsets of the multiple double-difference observation equations to obtain multiple sets of integer ambiguities and their corresponding baseline vector fixed solutions.
[0040] S103: If the difference between the maximum value and the minimum value in the multiple sets of baseline vector fixed solutions is less than or equal to a preset threshold, it is determined that the integer ambiguity parameters obtained by solving the multiple double-difference observation equations are fixed correctly.
[0041] For the sake of convenience, the following description will only be based on the server as the execution subject. The server mentioned in the present invention can be a server set up on a business platform, or a device such as a desktop computer or a laptop computer that can execute the solution of the present invention.
[0042] Figure 2 This is a schematic diagram of a specific implementation flow of an integer ambiguity detection method in the present invention, with reference to Figure 2 In one or more embodiments of the present invention, it can be assumed that there are n double-difference observation equations determined based on the data received by the receiver. Then, there are n different combinations of sub-subset double-difference observation equations (i.e., excluding one double-difference observation equation from the n double-difference observation equations). Let the index of the excluded observation equation i = 0, and store the result matrix b of the full set and sub-subset baseline solutions. all is an empty set, the general form of the double difference observation equation can be expressed as:
[0043] in, is the double-difference pseudorange observation value, is the double-difference carrier phase observation value, H b Design matrix for baseline vector, H ais the ambiguity design matrix, λ is the carrier wavelength, b is the baseline vector, a is the integer ambiguity vector, ε P is the pseudorange residual error, ε Φ is the phase residual error.
[0044] In each round of solution, the integer ambiguity can be firstly solved based on multiple double-difference observation equations; then, for each double-difference observation equation, the double-difference observation equation is eliminated, and the integer ambiguity is solved based on the remaining double-difference observation equations.
[0045] For example, we can determine whether i is equal to 0. If the condition is met, we can directly solve the integer ambiguity and baseline vector. If the condition is not met, we can eliminate the corresponding observation equation according to index i:
[0046] in, is the double-difference carrier phase observation value after removing the i-th row, H b,i Design the matrix for the corresponding baseline vector, H a,i Design matrix for the corresponding ambiguity, b i is the corresponding baseline vector, a i is the corresponding integer ambiguity vector, is the corresponding phase residual error.
[0047] It should be noted that when the index i=0 of the observation equation is eliminated, b0 and a0 are the fixed solution of the baseline vector and the integer ambiguity of the whole set respectively; otherwise, b i 、a i are the baseline vector fixed solutions and integer ambiguities of the sub-subsets respectively.
[0048] Regarding parameter estimation based on the double-difference observation equation, in one or more embodiments of the present invention, the parameter estimation here can be solved by any of the parameter estimation methods such as least squares method, Kalman filtering and graph optimization to obtain a floating-point solution for the ambiguity.
[0049] Then, the integer least squares method is used to solve the integer ambiguity a based on the ambiguity floating point solution. i , then update the baseline vector to fix the solution b i :
[0050] in, is the floating point solution of the baseline vector, is the covariance between the baseline vector float solution and the ambiguity vector float solution, is the variance of the floating-point solution of the ambiguity vector, is the floating-point solution for the ambiguity vector.
[0051] When the index i=0 of the observation equation is eliminated, is the floating-point solution of the baseline vector of the entire set, is the covariance between the full set of baseline vector float solutions and the full set of ambiguity vector float solutions, is the variance of the floating-point solution of the full set of ambiguity vectors, is the floating-point solution of the ambiguity vector of the entire set; otherwise, it is the relevant parameter of the secondary subset.
[0052] The baseline vector after each round of solution is fixed at b i Store in result matrix b all .
[0053] After each round of calculation, it can be judged whether i is equal to n. If the condition is not met, it will return to the beginning of the calculation and update i=i+1. If the condition is met, it will extract b respectively. all The maximum and minimum values of the three coordinate components are b max_row 、b min_row , and then perform the whole cycle ambiguity test: b max_row -b min_row ≤τ.
[0054] Among them, τ is the preset threshold.
[0055] If the integer ambiguity test is passed, the integer ambiguity parameters of the whole set are judged to be fixed correctly, and the fixed solution b0 of the baseline vector of the whole set is output; otherwise, the floating-point solution b0 of the baseline vector of the whole set is output.
[0056] Assuming that there are n double-difference observation equations, the baseline vector fixed solutions corresponding to n different sub-subset combinations can be obtained through the above calculation process of the baseline vector fixed solution, and b all The maximum and minimum values of the three coordinate components are b max_row 、b min_row , and then perform the whole cycle ambiguity test: b max_row -b min_row ≤τ.
[0057] When the difference between the maximum and minimum values in the multiple sets of baseline vectors is less than or equal to the preset threshold τ, the integer ambiguity parameters of the entire set are considered to be correctly fixed, and the baseline vector fixed solution b0 corresponding to the integer ambiguity obtained by solving multiple double-difference observation equations can be output to judge that the integer ambiguity parameters of the entire set are fixed correctly; when the difference between the maximum and minimum values in the multiple sets of baseline vectors is greater than the preset threshold, the baseline vector floating-point solution b0 obtained by solving multiple double-difference observation equations is output. In one or more embodiments of the present invention, the threshold value may be set to 0.015m.
[0058] Of course, the above-mentioned multiple calculations of the integer ambiguity and its corresponding baseline vector fixed solution using sub-subsets are only a feasible implementation method proposed by the present invention. Specifically, several double-difference observation equations are eliminated from the full set of multiple double-difference observation equations. The present invention does not impose any restrictions on this and can be determined according to actual applications.
[0059] based on Figure 1 The integer ambiguity verification method shown in this paper is based on the concept that more accurate integer ambiguity resolution leads to more stable integer ambiguity resolution. This method determines multiple observation equations based on data acquired by a receiver. Multiple integer ambiguity resolutions are performed based on the full set and multiple subsets of these observation equations. The stability of the integer ambiguity resolution is determined by comparing the difference between the maximum and minimum values of the baseline vector fixed solution in the multiple solution results with a preset threshold. If the integer ambiguity resolution is sufficiently stable, the corresponding integer ambiguity solution is accurate and effective, with high reliability, and can be accepted for subsequent applications. This method improves the reliability of the integer ambiguity verification method.
[0060] In summary, the present invention provides an ambiguity sub-subset consistency check method based on the observation value domain, which can ensure that the obtained integer ambiguity solution has a high reliability. Compared with the existing Ratio test, the algorithm proposed in the present invention can reduce the false positive problem caused by the Ratio test, further improve the success rate of integer ambiguity fixation, and achieve the purpose of enhancing the reliability of the baseline solution result. The present invention can be combined with other test methods such as the Ratio test to further reduce the false alarm rate of ambiguity and enhance the reliability of the baseline solution result. For example, the integer ambiguity test method of the present invention can be used in conjunction with the Ratio test. Only when both test methods pass simultaneously can the integer ambiguity be finally fixed, which can further improve the correct fixation rate of the integer ambiguity.
[0061] When applying the integer ambiguity checking method provided by the present invention, it is not necessary to Figure 1 The steps are executed in the order shown. The specific execution order of the steps can be determined according to needs, and the present invention does not limit this.
[0062] The above is an integer ambiguity checking method provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding integer ambiguity checking device, such as Figure 3 shown.
[0063] Figure 3 A schematic diagram of an integer ambiguity verification device provided by the present invention, comprising:
[0064] A construction module 201 is configured to determine a plurality of double-difference observation equations based on carrier phase observations and pseudorange observations of satellites received by a receiver;
[0065] A solving module 202 is configured to perform multiple integer ambiguity solutions based on the multiple double-difference observation equations and different subsets of the multiple double-difference observation equations, respectively, to obtain multiple sets of integer ambiguities and their corresponding fixed baseline vector solutions;
[0066] The verification module 203 is configured to determine that the integer ambiguity parameters obtained by solving the multiple double-difference observation equations are fixed correctly if the difference between the maximum and minimum values in the multiple sets of baseline vector fixed solutions is less than or equal to a preset threshold.
[0067] The specific definition of the integer ambiguity verification device can be found in the definition of the integer ambiguity verification method above and will not be repeated here. Each module in the aforementioned integer ambiguity verification device can be implemented in whole or in part via software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a computer device memory in software form, so that the processor can call and execute the corresponding operations of each module.
[0068] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 Provided integer ambiguity detection method.
[0069] The present invention also provides Figure 4 The structural diagram of the computer equipment shown in FIG. Figure 4 As shown in the figure, at the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 Provided integer ambiguity detection method.
[0070] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).
[0071] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present invention.
Claims
1. A method for checking integer ambiguity, characterized in that: include: Determine multiple double-difference observation equations based on carrier phase observation values and pseudo-range observation values of the satellite received by the receiver; According to multiple double-difference observation equations and different subsets of multiple double-difference observation equations, multiple integer ambiguity resolutions are performed to obtain multiple sets of integer ambiguities and their corresponding baseline vector fixed solutions; If the difference between the maximum and minimum values in the multiple sets of baseline vector fixed solutions is less than or equal to the preset threshold, it is determined that the integer ambiguity parameters obtained by solving the multiple double-difference observation equations are fixed correctly.
2. The integer ambiguity checking method according to claim 1, wherein: The performing of multiple integer ambiguity resolutions based on the multiple double-difference observation equations and different subsets of the multiple double-difference observation equations specifically includes: Integer ambiguity resolution is performed based on multiple double-difference observation equations; For each double-difference observation equation, the double-difference observation equation is eliminated, and the integer ambiguity is resolved based on the remaining double-difference observation equations.
3. The integer ambiguity checking method according to claim 1, wherein: Perform integer ambiguity resolution, including: Obtain floating-point solutions to ambiguities using any of the following methods: least squares, Kalman filtering, and graph optimization; The integer ambiguity is solved using the integer least squares method based on the ambiguity floating point solution.
4. The integer ambiguity checking method according to claim 1, wherein: The method further comprises: If the difference between the maximum and minimum values in multiple sets of baseline vectors is less than or equal to a preset threshold, the baseline vector fixed solution corresponding to the integer ambiguity obtained by solving multiple double-difference observation equations is output; If the difference between the maximum and minimum values in multiple groups of baseline vectors is greater than a preset threshold, the baseline vector floating-point solution obtained by solving multiple double-difference observation equations is output.
5. The integer ambiguity checking method according to claim 1, wherein: The preset threshold is 0.015m.
6. An integer ambiguity checking device, characterized in that: include: A construction module is used to determine a plurality of double-difference observation equations based on carrier phase observation values and pseudorange observation values of satellites received by a receiver; A solution module is used to perform multiple integer ambiguity solutions based on multiple double-difference observation equations and different subsets of multiple double-difference observation equations, so as to obtain multiple sets of integer ambiguities and their corresponding baseline vector fixed solutions; The verification module is used to determine that the integer ambiguity parameters obtained by solving multiple double-difference observation equations are fixed correctly if the difference between the maximum and minimum values in the multiple sets of baseline vector fixed solutions is less than or equal to a preset threshold.
7. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.
8. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 5 when executing the program.