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几种非线性滤波算法的性能分析

摘要: 非线性随机动态系统的滤波问题是一类经常遇到的实际应用问题,本文分析了扩展卡尔曼(EKF)、无迹卡尔曼滤波(UKF)和粒子滤波(PF)这三种非线性滤波算法的基本原理和特点以及适应的条件。并通过一个强非线性系统的实验仿真,验证了各自算法的性能。

Abstract: Filtering of nonlinear stochastic dynamic systems is a class of problems often encountered in practical applications. This article analyzes the basic principles, characteristics and adaptation conditions of the extended Kalman filter (EKF), unscented Kalman filter (UKF) and particle filter (PF). And also it verified the performance of these algorithms by experimental simulation of a strongly nonlinear system.

关键词: 非线性滤波;高斯滤波;扩展卡尔曼滤波;无迹卡尔曼滤波;粒子滤波

Key words: nonlinear filtering;Gaussian filtering;extended Kalman filter;unscented Kalman filter;particle filter

中图分类号:TN958文献标识码:A文章编号:1006-4311(2010)34-0190-02

0引言

对线性系统而言,最优滤波的闭合解就是著名的卡尔曼滤波;而对于非线性系统来说,要得到精确的最优滤波解是困难甚至不可能的,因为它需要处理无穷维积分运算。(剩余4161字)

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