Vehicle Target Tracking Method on FPDS

摘要：

There are many uncertain factors in vehicle target tracking, such as target appearance, target disappearance, rough weather, vehicle dither and so on. In order to deal with uncertainty of vehicle sensor data effectively, an improved Dempster-Shafer(D-S) evidential theory algorithm is proposed which is based on probability theory and fuzzy theory. Fuzzy probability Dempster-Shaffer (FPDS) vehicle tracing algorithm is formed. Reliability value of measuration and known target is calculated by FPDS, and the relation between measuration and track is determined by the maximum value of reliability function to improve the efficiency of data relevance. The FPDS is verified to be feasible to vehicle target tracking by Monte-Carlo algorithm.

作者: Yong Chen Xia Liu Qi Huang Chuanghua Zhang

作者单位: School of Automation Engineering, University of Electronic Science and Technology of China,610054 Ch School of Automation Engineering, University of Electronic Science and Technology of Ctuna,610054 Ch

会议类型: 国际会议

会议名称: Third International Symposium on Intelligence Computation and Applications(ISICA 2008)(第三届智能自动化、计算与制造国际研讨会)

会议地点: 武汉

会议语种:英文

页码: 120-122

在线出版日期: 2008-12-19（万方平台首次上网日期，不代表论文的发表时间）