A Particle Filter Algorithm based on Mixing of Prior probability density and UKF as Generate Importance Function

摘要：

　　As an important nonlinear filter theory,particle filter is a heated issue in domestic and foreign researches.The option of importance density is one of the key steps of particle filter algorithm.The proper option of importance density can minish the negative influence of filter algorithm caused by degeneracy problem.This paper introduces several widely-used options of importance density systemically,and analyzes their features and applied perspectives respectively.The paper also advances a comprehensive method of importance density,analyzes its technical features,explores the adjudgement and improvement of this method based on various performance,and finally puts forward the necessary further study according to the engineer requirements.

关键词： particle filter importance function SIS proposal distribution

作者: Liu Lu Juan Wang Meng Yang Shu Geng

作者单位: Department of Information Engineering and Computer Technology, Harbin Petroleum Institute,Harbin, He Haerbin Engineering University, Haerbin,China

会议类型: 国际会议

会议名称: 2015 International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2015)(2015 机械,电子与信息技术工程国际会议)

会议地点: 重庆

会议语种:英文

页码: 403-406

在线出版日期: 2015-03-02（万方平台首次上网日期，不代表论文的发表时间）