Multiple Model Rao–Blackwellized Particle Filter

摘要：

In this paper,we proposed a new multiple model Rao–Blackwellized particle filter (MMRBPF) based algorithm for maneuvering target tracking.The advantage of the proposed approach is that the Rao-Blackwellization allows the algorithm to be partitioned into target tracking and model selection sub-problems,where the target tracking can be solved by the probabilistic data association filter,and the model selection by sequential importance sampling.The analytical relationship between target state and model is exploited to improve the efficiency and accuracy of the proposed algorithm.Finally,the experiment results show that the proposed algorithm results in more accurate tracking than the existing one.

作者: Li Liang-qun Xie Wei-xin Huang Jing-xiong

作者单位: School of Information Engineering,Shenzhen University,Guangdong 518060,China

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）