%0 Journal Article
%T Enhanced multiple model particle filter for maneuvering target tracking<br>改进的多模型粒子滤波机动目标跟踪算法
%A JIAN Fu-sheng
%A XU Yue-min
%A YIN Ze-jie
%A <br>鉴福升
%A 徐跃民
%A 阴泽杰
%J 控制理论与应用
%D 2010
%I 
%X Classical multiple model particle filters(MMPF) can not effectively control particles of each mode in maneuvering target tracking. An enhanced multiple model particle filter(EMMPF) algorithm is proposed, which estimates the mode and state independently. The posterior probability of each mode is updated with the associate likelihood function. The number of particles of each mode is given in advance according to the mode property and is kept constant in the recursion. Simulation shows that the EMMPF achieves better tracking accuracy with fewer particles.
%K particle filter
%K multiple model
%K tracking algorithm
%K number of particles
%K likelihood function<br>粒子滤波
%K 多模型
%K 跟踪算法
%K 粒子数
%K 似然函数
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=4E7B9E91AC971A5DAD813F306126DCB1&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=85873A559EE29055&eid=7AD2D1CE7CD34BB7&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=7