计算机工程与科学2012，Vol.34Issue(7)：136-139,4.DOI:10.3969/j.issn.1007-130X.2012.07.025
非高斯噪声中的粒子滤波算法研究
Research on Particle Filter Algorithms in the Non-Gassian Noise
摘要
Abstract
The particle filter has become the mainstream method for solving system parameter estimation and the state of filter in nonlinear non-gaussian dynamic systems. However the particle degradation problem in particle filter is an inevitable phenomenon and the solution is particle resampling. According to the particle degradation phenomenon of the existing defects, there will be a new mixed particle filter proposed in this paper based on the extended Kalman particle filter. In the new algorithm* the extended Kalman particle filter with support vector machine (SVM) implements the present moment sampling and resampling. This structure makes use of the latest observation information avoiding the lack of particles. It has small errors and better stability. Theoretical analysis and simulation results show that the new method outperform the interacting standard particle filter and the extended Kalman particle filter in the filter precision of double-modal noise system state.关键词
粒子滤波/重采样/支持向量机/双模噪声Key words
particle filter/resampling/SVM/double-modal noise分类
信息技术与安全科学引用本文复制引用
王晓薇,山拜·达拉拜,陈娟,李婷婷..非高斯噪声中的粒子滤波算法研究[J].计算机工程与科学,2012,34(7):136-139,4.基金项目
国家自然科学基金资助项目(60971130) （60971130）
