Title :
A Possibilistic Data Association Based Algorithm for Multi-target Tracking
Author_Institution :
Inner Mongolia Univ. of Sci. & Technol., Baotou, China
Abstract :
The reasons for fuzzy data association in a densely cluttered environment are analyzed in this paper, and a possibilistic data association based algorithm for multi-target tracking is proposed. This paper fully analyses the shortcomings of the conventional fuzzy approaches and proposes the possibilistic data association based algorithm which can improve the performance of the multiple targets tracking. It can reduce the association errors caused by clutters greatly. The simulation results show that the algorithm has superiority over the conventional fuzzy approaches, and can track multiple targets in real time.
Keywords :
fuzzy set theory; sensor fusion; target tracking; conventional fuzzy approach; fuzzy data association; multi-target tracking; possibilistic data association; Algorithm design and analysis; Clustering algorithms; Clutter; Joints; Real-time systems; Signal processing algorithms; Target tracking; data association; fuzzy C-mean clustering; joint probability data association; multi-target tracking; possibilistic clustering;
Conference_Titel :
Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4673-4893-5
DOI :
10.1109/ISDEA.2012.43
