Particle Estimation Algorithm Using Angle between Observation Vectors for Nonlinear System State  

作　　者：LIANG Jun LIANG Jun PENG Yu PENG Yu PENG Xiyuan[1] PENG Xiyuan[1] 

机构地区：[1]Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150080, China [1]Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150080, China

出　　处：《Chinese Journal of Electronics》2009年第4期700-702,共3页电子学报（英文版）

摘　　要：A particle estimation algorithm where the weight of the particle is related to angle between observa- tion vectors is presented for nonliear system state. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than Sequential importance resampling （SIR）, Auxiliary particle filter （APF）, Regu- larized particle filter （RPF）, and Gaussian particle filter （GPF）.

关 键 词：Nonliear system State estimation Par- ticle filter Sequential importance resampllng （SIR）~ Aux- iliary particle filter （APF） Regularized particle filter （RPF） Gaussian particle filter （GPF）. 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置] TP301.6[自动化与计算机技术—控制科学与工程]