A Particle Filter Algorithm Based on SSUKF

摘要：

As an important nonlinear filter theory，the particle filter(PF) is a heated issue in domestie and foreign reseaches．The optlon of importance denslty and resampHng are the key steps of particle fiIter algorithm．The appHcation of UKF algorithm based on SSUT to create the importance probability density function(PDF)．with the particle swarm optimization(PSO)，can form a new algorithm of particle filter(PSO-SSUPF)．PSO can make the patlcles move to high likelihood area before the weights updating．Consequently, sample lmpoverishment can be restralned to some extent．With the SSUT cutting down the number of slgma points．the efficlency of the algorithm can be considerably improved in the eondition of ensuring the precision being similar with standard UPF，and its performance is confirmed With the simulation．

关键词： PF PSo SSUT Improtance density

作者: Meng Yang Wei Gao

作者单位: Automation College Harbin Engineering University Harbin, Heilongjiang Province, China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）