Whole-cycle ambiguity correctness checking method based on integrity monitoring

Abstract

The invention belongs to the technical field of satellite precise navigation and positioning, and specifically relates to a whole-cycle ambiguity correctness checking method based on integrity monitoring capable of improving the reliability of satellite navigation and positioning. The method comprises the following steps: counting detection quantity and a probability density distribution model of the detection quantity under fault-free hypothesis and fault hypothesis in an observed quantity domain by constructing an ambiguity floating solution and an ambiguity fixed solution, and competing correctness checking for the ambiguity floating solution in the observed quantity domain; carrying out decorrelation treatment in an ambiguity space, using the floating solution as the center of the ambiguity fixed solution, searching and obtaining in the determined range of a variance-covariance matrix after decorrelation, and completing difference checking for the ambiguity floating solution and the ambiguity fixed solution. According to the method, the resolving success rate is maximized by adjusting the combined scheme of the observed quantity and adjusting an ambiguity organization region.

Description

technical field [0001] The invention belongs to the technical field of satellite precision navigation and positioning, and in particular relates to a integrity monitoring-based integrity monitoring-based integrity-monitoring method for checking the correctness of the whole circle ambiguity, which improves the reliability of satellite navigation and positioning. Background technique [0002] The resolution of the integer ambiguity and its correctness check are one of the key technologies for the differential carrier phase technology to achieve high precision and high reliability. To this end, Professor Teunissen proposed the LAMBDA algorithm that can quickly solve the integer ambiguity, and proposed to implement the correctness test for the integer ambiguity solution, which needs to use the hypothesis testing theory to pass at least three testing steps: (i) ambiguity Availability detection of floating-point solution; (ii) difference test between floating-point solution and fi...

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Problems solved by technology

Focusing on these three key issues, although relevant researchers at home and abroad have proposed relatively complete integer ambiguity testing models and theories, there are still certain defects in various testing models: first, the optimal solution and In the inspection of suboptimal solutions, the ratio test (ratio test) has become a commonly used method, but the ratio test not only ignores the correlation between the optimal integer ambiguity and the suboptimal integer ambiguity, but also makes step (Ⅲ) The theoretical assumptions of testing based on the ideal distribution model are no longer reliable, and the selection of various detection thresholds in the testing process depends on empirical values, lacking a strict theoretical basis

Secondly, in the correctness test of the final fixed solution of ambiguity, one of the important indicators widely used to evaluate the correctness performance is the success rate of ambiguity resolution. However, the calculation model of the traditional solution success rate has at least two deficiencies: On the one hand, due to the correlation between the fixed ambiguity solutions, the ambiguity pull-in region that affects the success rate of the solution is narrow and long. The determination of the solution takes more time, and the real-time performance of the solution is difficult to be satisfied; on the other hand, only when the solution success rate is sufficiently close to 1, the corresponding ambiguity solution is acceptable, but for this close The extent of 1 cannot be effectively measured

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