Data Association Algorithm Based on Improved Fuzzy C-means for Multi-target Tracking

摘要：

A new data association algorithm based on improved fuzzy c-means (TFMC) for multi-target tracking in a cluttered environment was proposed. Firstly, the proposed algorithm was used to cluster the received measurements and then by introducing the conception of the fuzzy membership degree, the partition matrix of measurements to track is constructed. The proposed approach has a lower computational complexity in the expense of a little lower performance compared to the JPDA algorithm. Simulation results show that the arithmetic is an effective solution with less calculation to precision of association between measurements and measurements for multiple targets in a cluttered environment.

关键词： multitarget tracking data association improved fuzzy C-means

作者: Wang Yue-long Ma Fu-chang

作者单位: College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan, China Institute of Measuring and Controlling Technology Taiyuan University of Technology Taiyuan, China

会议类型: 国际会议

会议名称: 2011 International Conference on Electronics and Optoelectronics(2011电子学与光电子学国际会议 ICEOE 2011)

会议地点: 大连

会议语种:英文

页码: 846-850

在线出版日期: 2011-07-29（万方平台首次上网日期，不代表论文的发表时间）