A Possibilistic Data Association Based Algorithm for Multi-target Tracking

Author

Liang Hao

Author_Institution

Inner Mongolia Univ. of Sci. & Technol., Baotou, China

fYear

2013

fDate

16-18 Jan. 2013

Firstpage

158

Lastpage

162

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ISDEA.2012.43

Filename

6454673