非线性确定采样型滤波器采样点优化算法

吴青坡; 丛源材; 周绍磊

doi:10.15892/j.cnki.djzdxb.2016.05.035

2016 , Vol. 36 >Issue 5: 137 - 141

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2016.05.035

摘要

采样点的选取对确定采样型滤波器的精度和稳定性起着决定性作用,为提高滤波器的数值稳定性,首先,采用协方差矩阵分解方法对获得的采样点进行优化,解决了数值大小对采样点离采样中心距离的影响问题;其次,通过选择合适的正交变换,在不改变滤波精度的前提下消除了采样点中存在的非局部效应;最后,利用一个落体跟踪模型对所提基于采样点优化方法的确定采样型滤波器进行仿真分析,仿真结果验证了该采样点优化方法的有效性。

关键词： 确定采样型滤波器; 采样点优化; 协方差矩阵分解; 正交变换

本文引用格式

吴青坡 , 丛源材 , 周绍磊 . 非线性确定采样型滤波器采样点优化算法[J]. 弹箭与制导学报, 2016 , 36(5) : 137 -141 . DOI: 10.15892/j.cnki.djzdxb.2016.05.035

Abstract

The selection of sample points plays a decisive role on the accuracy and stability of filter during the filter process of deterministic sampling filters. In order to improve the numerical stability of the filter, the obtained sampling points was optimized by covariance matrix decomposition, which solves the problem of the numerical influence on the distance between sample points and the mean Then the appropriate orthogonal transformation is used to eliminate the non-local effect, and it will not change the accuracy of filter under invariant theory. Finally, the effectiveness of the sample points optimization technique is validated through the simulation of a tracking problem

Key words： deterministic sampling filters; sampling points optimization; covariance matrix decomposition; orthogonal transformation

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