LLL (Lenstra-Lenstra-LovaszLattice) ambiguity decorrelation algorithm

Abstract

The invention discloses an LLL (Lenstra-Lenstra-LovaszLattice) ambiguity decorrelation algorithm. According to the algorithm, upper triangular decomposition (U<T>U) is performed on a covariance matrix Qa through utilizing Cholesky decomposition method, so that an upper triangular matrix U<T> can be obtained, and with the above decomposition method adopted, the computational efficiency of the LLL algorithm can be improved; before algorithm decomposition every time, descending sorting is performed on column vectors of the matrix Qa according to the magnitude of inner products, and a coefficient matrix can obtain a minimum integer value, and the decorrelation performance of the decorrelation algorithm is better; and a rounding step in an orthogonal transformation process is shifted to a Z-solving matrix, and therefore, calculation quantity increase and error accumulation caused by repeated rounding in an iteration process can be avoided, and the computational efficiency and success rate of the novel algorithm can be improved.

Description

technical field [0001] The invention belongs to the technical field of satellite navigation and positioning, and relates to an ambiguity reduction correlation algorithm, in particular to an LLL ambiguity reduction correlation algorithm used in GNSS integer ambiguity resolution. Background technique [0002] In the process of high-precision real-time positioning using GNSS carrier phase as the observation quantity, it is a key issue to solve the integer ambiguity quickly and accurately. Down-correlation processing is a commonly used method with excellent performance. Because the correlation of the ambiguity covariance directly determines the speed and efficiency of the whole ambiguity solution, and affects the effect and success of the ambiguity solution, therefore, a fast and efficient de-correlation algorithm is proposed to reduce the original ambiguity correlation 1. The key to realizing GNSS high-precision real-time positioning is also the purpose and significance of t...

AI Technical Summary

Problems solved by technology

Among them, the LLL algorithm is a relatively novel ambiguity reduction algorithm, which has been deeply researched and widely used in recent years, but there are still some defects, such as rounding errors in the process of integer orthogonal transformation. The continuous accumulation during the iterative process will affect the convergence of the algorithm, and even lead to the failure of the drop-correlation

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