基于均值漂移交互多模型粒子滤波算法  

Mean Shift IMM Paticle Filtering Based on Mean Shift IMM for Target Tracking

作　　者：陈国良 康健[2] 张仲凯 芮国胜[2] 

机构地区：[1]解放军92155部队 [2]海军航空工程学院 [3]解放军91640部队

出　　处：《火力与指挥控制》2011年第12期31-33,共3页Fire Control & Command Control

基　　金：国家自然科学基金资助项目(60541001)

摘　　要：针对交互多模型粒子滤波计算量大的问题,将视觉跟踪领域的均值漂移算法(Mean Shift)与交互多模粒子滤波(PF)算法相结合,该算法利用均值漂移算法在重采样之后将粒子收敛到靠近目标真实状态的区域内,在提高定位精度的同时减少所采用的粒子数,减少了算法的运行时间。通过被动跟踪仿真实例,同时使用均值漂移粒子滤波与传统粒子滤波进行跟踪仿真,分析了跟踪性能,利用均方根误差比较了误差性能。结果表明,新算法具有更高的跟踪精度,并且运行时间显著减少。To reduce the computation burden of IMMPF,the Mean Shift and particle filter were combined.The mean shift technique was used to estimates the gradient of the approximated density and moved particles toward the modes of the posterior,leading to a more effective allocation of particles thereupon fewer particles were needed and the computational demand was reduced.The performance were analyzed by comparison with the IMM-PF.Simulation results show that IMM-MSPF algorithm can reduce computation burden.Further more,the track accuracy of the algorithm can also be effectively improved.

关 键 词：均值漂移 粒子滤波 被动跟踪 

分 类 号：TN953[电子电信—信号与信息处理]