Multisensor Multitarget Tracking Based on a Matrix Reformulation of the GM-PHD Filter

摘要：

　　The Probability Hypothesis Density(PHD)filter is a more tractable alternative to the Random Finite Set(RFS)based optimal multitarget Bayes recursion.In this paper,a matrix reformulation of the Gaussian Mixture PHD(GM-PHD)filter is introduced.Thus a new multisensor GM-PHD filter is constructed based on the matrix reformulation.Simulation results show it can be used in some applications when the sequential GM-PHD filter fails,and outperforms the sequential GM-PHD filter when those sensors have poor detection probabilities.

关键词： Finite Set Statistics(FISST) GM-PHD Multitarget tracking Multisensor PHD

作者: Hongjian Zhang Yuewu Zhang Bei Ye Jin Wang

作者单位: Air Force Military Representative Office in Shanghai Area.,Shanghai 201601

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 2026-2032

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）