A STUDY ON MULTI-TARGET TRACKING AND PHD FILTER

摘要：

The probability hypothesis density (PHD) filter as an efficient, practical and robust approach to solve the multi-target tracking problem has been successfully implemented.In this paper, a study on multi-target tracking problem and the PHD filter with lateral and vertical thinking is proposed.Firstly we list several difficulties (data association, time-varying number, and inaccessible control signal) for multitarget tracking; and then come up with the particle PHD filter as an alternative, while summarizing the algorithm with clarity and perception; finally simulation and analysis further prove the strengthens of PHD filter.

关键词： Multi-target tracking Random finite sets Bayesian filtering Particle PHD filter

作者: PENG QI LU WANG

作者单位: Center for Autonomous Systems School of Computer Science and Communication KTH Royal Institute of Technology,10044 Stockholm,Sweden

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer Technology and Development(2011第三届计算机技术与发展国际会议 ICCTD2011)

会议地点: 成都

会议语种:英文

页码: 1596-1601

在线出版日期: 2011-11-25（万方平台首次上网日期，不代表论文的发表时间）