电子学报2017，Vol.45Issue(2)：300-306,7.DOI:10.3969/j.issn.0372-2112.2017.02.006
基于空间分布和时间序列分析的粒子滤波算法
An Improved Particle Filter Based on Space Distribution and Time Series Analysis
摘要
Abstract
In order to solve the problem of sample particles impoverishment,an improved resampling particle filter is presented.It is based on the space distribution and time series analysis.The most important particle that has higher temporal correlation between the particle's path and observation path in particle propagating is chosen.It can avoid the problem in the traditional resampling algorithm that only the particle's weights are considered,and the low weighed particles have the risk to be thrown away.Thus the problem of particles impoverishment is weakened and the estimate accuracy is improved.By the two-sample Kolmogorov-Smirnov Test,a proof is given that the particles that are resampled by the improved algorithm and the original particles belong to the same distribution.The proposed approach,verified by simulations,indicates that its accuracy is better than traditional methods for the nonlinear system state estimation,especially when the number of initial sampiing particles is small.关键词
非线性估计/残差重采样/时间序列分析/柯尔莫哥洛夫-斯米尔诺夫检验Key words
nonlinear estimation/residual resampling/time series analysis/Kolmogorov-Smirnov test分类
信息技术与安全科学引用本文复制引用
杨伟明,赵美蓉,黄银国,李瀚辰..基于空间分布和时间序列分析的粒子滤波算法[J].电子学报,2017,45(2):300-306,7.基金项目
国家自然科学基金青年科学基金(No.61304246) （No.61304246）
天津市高等学校科技发展基金(No.20130707) （No.20130707）
