%0 Journal Article
%T The hybrid annealed particle filter<br>混合退火粒子滤波器
%A Du Zheng-Cong
%A Tang Bin
%A Li Ke
%A <br>杜正聪
%A 唐斌
%A 李可
%J 物理学报
%D 2006
%I 
%X In this paper, a new particle filter based on sequential importance sampling (SIS) is proposed for the on-line estimation of non-Gaussian nonlinear systems. In this filtering method, state parameters separation and an annealing parameter are used to produce importance function. Since the distribution function makes full use of the prior, likelihood, and statistical characteristics of noise and the newest observation data, it is much closer to posterior distributions. Theoretical analysis and simulation show that the performance of proposed particle filter outperforms the standard particle filter and the extended Kalman filter.
%K non-linear
%K non-Gaussian
%K particle filter
%K sequential importance sampling<br>非线性
%K 非高斯
%K 粒子滤波
%K 序贯重要性抽样
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=6E709DC38FA1D09A4B578DD0906875B5B44D4D294832BB8E&cid=47EA7CFDDEBB28E0&jid=29DF2CB55EF687E7EFA80DFD4B978260&aid=419755CA76CA36DD&yid=37904DC365DD7266&vid=E514EE58E0E50ECF&iid=38B194292C032A66&sid=E6D5A068841F33F3&eid=F0CB1CC137DFCF2D&journal_id=1000-3290&journal_name=物理学报&referenced_num=4&reference_num=10