基于全球导航定位系统(Global Navigation Satellite System,GNSS)载波相位差分技术的高精度姿态测量中,整周模糊度快速求解是制约测姿性能的核心,为改进测姿数据处理中计算效率和精度上的矛盾,本文提出了一种基于粒子群优化模糊度搜索的GNSS实时测姿算法.新算法将带有自适应掠动策略的蚁群进化思想应用于整周模糊度搜索,可免除模糊度去相关处理步骤,直接进行整周模糊度搜索,并能改善收敛速度慢和陷人局部最优解的问题,从而提高算法的自适应能力.实验分析表明:相比传统处理技术,新算法对模糊度固定解的搜索效率和成功率显著提高,用于动静态载体测姿计算,实时性也可以提升,工程应用前景较好.%Rapid resolution of ambiguity is the core problem of GNSS attitude determination, when carrier phase difference technique is used for high-precision attitude measurement. To improve the computational efficiency and accuracy of the attitude measurement data processing, GNSS real-time attitude determination algorithm based on particle swarm optimization for ambiguity search is discussed in this paper. This algorithm applies ant colony evolving idea with adaptive sweep strategy for ambiguity search, which can eliminate the ambiguity de-correlation processing step, and improve the convergence speed and local maximum problems, so as to improve the adaptive ability of the algorithm. The experimental results show that compared with the traditional processing technology, the new algorithm improved the search efficiency and success rate of ambiguity fixed solution. It can be used to improve the real-time performance of carrier phase and engineering application.
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