基于交互式多模型的粒子滤波算法  

Particle Filter Based on Interacting Multiple Model

作　　者：邓小龙[1] 谢剑英[1] 杨煜普[1] 

机构地区：[1]上海交通大学自动化系,上海200030

出　　处：《系统仿真学报》2005年第10期2360-2362,2380,共4页Journal of System Simulation

基　　金：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。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.

关 键 词：交互式多模型 粒子滤波 非线性 非高斯 重抽样 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]