PARTICLE FILTERING FOR MANEUVERING TARGET TRACKING IN CLUTTER

摘要：

In this paper,we introduce the mixed particle filtering PDA(MPF-PDA)algorithm，an efficient variant on the PF for nonlinear maneuvering target tracking in clutter.Each particle samples a discrete mode and approximates the continuous state by a Gaussian distribution which is updated by a combination of the Unscented Kalman filter (UKF) and PDA.The discrete mode is estimated by an improved PF combined with PDA.The posterior distribution of the target state is approximated with a mixture of Gaussians.Monte Carlo simulations show performance improvement of the proposed algorithm over traditional bootstrap particle filtering，and the superiority for large clutter densities.

关键词： particle filtering unscented Kalman filer probabilistic data association target tracking

作者: Xiaojun Yang Kunlin Shi Jinping Guo

作者单位: School of Science Engineering,Changan University,Post Code:710064,Xian,China;Xian Institute of El Xian Institute of Electromechanical Information Technology,Post Code:710065,Xian,China

会议类型: 国际会议

会议名称: The 6th International Conference on Applied Electrostatics(第六届国际静电应用会议)

会议地点: 上海

会议语种:英文

页码: 188-191

在线出版日期: 2008-11-03（万方平台首次上网日期，不代表论文的发表时间）