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基于交互式多模型的粒子滤波算法
引用本文:邓小龙,谢剑英,杨煜普.基于交互式多模型的粒子滤波算法[J].系统仿真学报,2005,17(10):2360-2362,2380.
作者姓名:邓小龙  谢剑英  杨煜普
作者单位:上海交通大学自动化系,上海,200030
基金项目:国家863基金资助项目(2001AA422420-02)
摘    要:融合交互式多模型和粒子滤波,提出了一种新的多模型粒子滤波算法。该算法采用多模型结构以跟踪目标的任意机动。各模型采用粒子滤波算法,以处理非线性、非高斯问题。各模型中相对固定数目的粒子群经过相互交互、粒子滤波后再进行重抽样以减少滤波退化现象。与通用的交互式多模型算法进行了比较,试验仿真结果证实了本文新滤波算法的有效性。

关 键 词:交互式多模型  粒子滤波  非线性  非高斯  重抽样
文章编号:1004-731X(2005)10-2360-03
收稿时间:2004-09-09
修稿时间:2004-09-092005-03-18

Particle Filter Based on Interacting Multiple Model
DENG Xiao-long,XIE Jian-ying,YANG Yu-pu.Particle Filter Based on Interacting Multiple Model[J].Journal of System Simulation,2005,17(10):2360-2362,2380.
Authors:DENG Xiao-long  XIE Jian-ying  YANG Yu-pu
Abstract:Combining interacting multiple model with particle filter, a new multiple model particle filter is presented. The algorithm used the multiple models to track arbitrary maneuvering of the target. Every model used particle filter to deal with the nonlinear and non-Gaussian problems, After interaction and particle filtering, particles in the models with the fixed number are resampled to reduce the degeneracy of filtering, In the simulations, compared with the general interacting multiple model, the results demonstrate the efficiency of the new filtering method.
Keywords:interacting multiple model  particle filter  nonlinear / non-Gaussian  resampling
本文献已被 CNKI 维普 万方数据 等数据库收录!
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