A Fast Search Algorithm for Integer Ambiguity Under Baseline Length Constraint

Abstract

The invention provides a fast search algorithm for integer ambiguity under the constraint of baseline length, which belongs to the technical field of satellite navigation and positioning. Reduce the time consumption of the ambiguity search process in CLAMBDA, and ensure a high solution efficiency while the ambiguity resolution has a high success rate. It is an improvement on the existing full-circle ambiguity search algorithm under the baseline length constraint. , and further improved the CLAMBDA theoretical solution system to ensure a high solution success rate, and at the same time, it can significantly improve the ambiguity solution efficiency, thereby improving the accuracy of satellite navigation and positioning to meet the requirements of real-time, fast and high-precision relative positioning need.

Description

technical field [0001] The invention belongs to the technical field of satellite navigation and positioning, and in particular relates to a fast search algorithm for integer ambiguity under the constraint of baseline length. Background technique [0002] In attitude measurement, the baseline length between GNSS antennas can be accurately measured in advance, and is often used as prior information to participate in baseline processing and ambiguity resolution, so as to improve the success rate of ambiguity resolution, thereby improving the accuracy of satellite navigation and positioning. precision. [0003] According to the use of baseline length information, the following three types of methods are commonly used: discriminant condition method (Li Zhenghang et al., 2007), observation equation joint solution method (Liu Genyou et al., 2003), and integer least squares method with quadratic constraints (Park&Teunissen et al. ,2003). Among them, the integer least squares metho...

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Problems solved by technology

[0004] Although the CLAMBDA method has the advantage of a high solution success rate, the ambiguity search space does not have the property of a hyperellipsoid because the baseline component has prior information, so its search process is different from the conventional LAMBDA method, and it needs to The ambiguity search algorithm for further research

[0005] The main problems in the current CLAMBDA method are: 1) The objective function for solving ambiguity is a mixed quadratic type of ambiguity and baseline components, which may lead to an excessively large search space, greatly increasing the time-consuming search, and making it difficult to quickly and effectively obtain Integer ambiguity vector; 2) Most of the existing methods are weighted constraints on the baseline length information, and the nonlinear least squares method is used to solve the baseline, but the specific solution process of the baseline solution under the strong constraint model is different from that of the weighted constraint model , its theory needs to be further enriched and perfected

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