Track Association for B-spline Gaussian Mixture PHD Filter using Shape Information

摘要：

　　The B-spline Gaussian mixture probability hypothesis density(BS-GM-PHD)filter can track an unknown number of extended targets and estimate their shape.However,the target tracks might be inaccurately associated when targets are closely spaced.This paper presents a novel track association approach for the BS-GM-PHD filter using the estimated shape information.First,a shape table(ST)will be established to keep the shape information of each estimated target.Then,targets will be identified by using the ST.the simulation results show that the proposed approach can accurately associate tracks,even though the targets are closely spaced.

关键词： track association PHD filter extended target tracking

作者: Peng Li Hongwei Ge Wenhui Wang

作者单位: Key Laboratory of Advanced Process Control for Light Industry(Jiangnan University),Ministry of Education,Wuxi,214122,China;School of Internet of Things Engineering,Jiangnan University,Wuxi,214122,China

会议类型: 国际会议

会议名称: 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference(ITOEC2017)(2017 IEEE 第3届信息技术与机电一体化工程国际学术会议)

会议地点: 重庆

会议语种:英文

页码: 629-633

在线出版日期: 2017-10-03（万方平台首次上网日期，不代表论文的发表时间）