Data association for extended target tracking by BP. Issue 12 (1st December 2018)

• Record Type: Journal Article
• Authors: Su, Zhenzhen; Ji, Hongbing; Zhang, Yongquan
• Is Part Of: IET radar, sonar & navigation. Volume 12:Issue 12(2018)
• Page Start: 1484
• Page End: 1492
• Publication Date: 2018-12-01
• Subjects: trees (mathematics) -- sensor fusion -- target tracking -- probability; BP -- multiple extended target tracking -- point target tracking -- graphical model formulation -- tracking efficiency -- simplified measurement set -- joint probabilistic data association -- data association algorithm -- belief propagation -- minimal spanning tree algorithm; Signal processing -- Periodicals; Radar -- Periodicals; Sonar -- Periodicals; Electronics in navigation -- Periodicals; Navigation -- Periodicals; 621.3848
• DOI: 10.1049/iet-rsn.2018.5273
• Languages: English
• ISSNs: 1751-8784

Abstract

Abstract : Data association with great efficiency is an important problem in multiple extended target tracking. It is more challenging than that in point target tracking as the measurements of extended targets are more. This study presents a graphical model formulation of data association for extended target tracking, which is solved by belief propagation (BP) to obtain estimations. To construct the graphical model, a simplified scheme for measurements is proposed to improve the tracking efficiency, which is based on minimal spanning tree algorithm. Then, the data association problem according to the simplified measurement set is presented, solved by BP. Finally, experiment results show the proposed algorithm has advantages over the algorithm based on joint probabilistic data association and the previous data association algorithm, introduced by Vivone and Braca, in terms of robustness and efficiency.