一种改进粒子滤波算法分析

在非线性、非高斯系统的状态估计研究中,最常用的是EKF和UKF两种方法,但是这两种方法还局限于高斯分布的情况。在之后的研究中出现了不受非线性、非高斯分布问题限制的粒子滤波算法。这种算法的主要问题是粒子退化问题,常规的再采样方法虽然可以解决退化问题,但是容易导致粒子耗尽。针对这种问题,本文提出用辅助变量粒子滤波算法,对标准粒子滤波算法步骤中的再采样部分进行改进,最后对算法进行性能仿真及分析。仿真结果表明,改进的粒子滤波算法性能良好。

Analysis of an improved particle filter algorithm

In the non-linear,non-Gaussian system state estimation studies,the commonly used methods are EKF and UKF,which is limited to Gaussian distribution.In the later study,the particle filter algorithm is proposed in the research of non-linear,non-Gaussian systematic.Degeneracy phenomenon is a main disadvantage to particle filter application,common resampling methods can resolve degeneracy phenomenon,but the sample impoverishment is deduced.Therefore,this paper is presented auxiliary variable PF to improve the pa...