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在全面分析粒子滤波原理的基础上,提出一种改进高斯粒子滤波方法.该方法利用确定性采样滤波算法进行时间更新,替代高斯粒子滤波算法中的随机采样过程;另外,针对厚尾噪声情况,利用鲁棒统计方法对确定性采样滤波方法进行鲁棒性改进,并将其应用于所提出的改进高斯粒子滤波.将粒子滤波算法应用于交会对接相对导航问题,仿真结果表明,在多种测量噪声情况下,改进高斯粒子滤波较其他粒子滤波,能够在不过多损失估计精度的同时有效降低计算量.文中的研究成果为将粒子滤波应用于航天器导航问题提供了理论参考.
On the basis of a comprehensive analysis of the principle of particle filter, an improved Gaussian particle filter method is proposed, which uses deterministic sampling filter algorithm to update time and replaces the random sampling process in Gaussian particle filter algorithm. In addition, Robust statistical method is used to improve the robustness of the deterministic sampling filtering method and its application to the proposed improved Gaussian particle filter.The particle filter algorithm is applied to the relative navigation problem of rendezvous and docking, the simulation results show that, in a variety of measurements Under the condition of noise, the improved Gaussian particle filter can filter less than the other particles without losing too much estimation accuracy.The research results in this paper provide a theoretical reference for the application of particle filter in spacecraft navigation.