Using Target Radial Length for Data Association in Multiple-Target Tracking

摘要：

Data association plays an important role in multi-target tracking. The traditional data association algorithm uses the nearest neighbor distance method. It will make mistake in larger echo density. Feature aided data association algorithm is tend of development in multi-target tracking. Incorporating target kinematics information and feature information can increase the information dimension, and enhance the association accuracy. In this work, feature aided nearest neighbor algorithm based on radial length of target is proposed. Comparing the traditional data association algorithm, the proposed algorithm can increase the times of correct association when targets move in parallel or move crosswise, and improve the performance of data association algorithm for multi-target tracking.

关键词： high resolution range profiles(HRRP) radial length data association feature aided tracking nearest neighboralgorithm

作者: ZHAO Feng ZHAO Hong-zhong HUANG Meng-jun QIU Wei

作者单位: ATR Key Lab, National University of Defense Technology, Changsha, China, 410073

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 2257-2260

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）