会议专题

A Modified Scaled Joint Probability Data Association Algorithm

A modified Joint Probabilistic Data Association algorithm is proposed in this paper to avoid track coalescence. Above all, an arbitrary positive scaling factor will be employed to multiply the maximum probabilities of every target associated with measurements. Then an exclusive measurement is defined for every target in the new algorithm, which is the maximum probability measurement associated with the target. The association probabilities of exclusive measurement with other targets except corresponding target are set at 0. At last, the association probabilities of every measurement will be given weights by means of the Entropy Value Method in the new algorithm. The simulation results show that the new algorithm can effectively solve the track coalescence problem in all kinds of scenarios and its track performance is better than the Joint Probabilistic Data Association algorithm’s.

Joint Probabilistic Data Association track coalescence exclusive measurement Entropy Value Method

Xu Yi-bing Chen Song-lin Wen Yu Zhu Min

Xi’an Communications InstituteXi’an, China Xi’an Communications Institute Xi’an, China

国际会议

2011 International Conference on Information System and Computational Intelligence(2011 IEEE信息系统与计算智能国际会议 ICISCI 2011)

哈尔滨

英文

94-98

2011-01-18(万方平台首次上网日期,不代表论文的发表时间)