DocumentCode :
1868013
Title :
Random sets in data fusion: a new framework for multitarget tracking
Author :
Wen, Chenglin ; Xu, Xiaobin
Author_Institution :
Hangzhou Dianzi Univ.
fYear :
2006
fDate :
19-21 Jan. 2006
Lastpage :
1004
Abstract :
Although a connection between multitarget tracking and random set theory was recognized during the course of development of the indirect-estimation tracking algorithms, it was only recently that such a connection started to be discussed based on random set theory. In this paper, the limitation of the traditional multitarget tracking framework was discussed, firstly, which separates tracking system into several estimation subproblems to solve respectively, and then, the early-stage direct-estimation tracking approach affinitive with random set theory is summarized. Ultimately this paper presents random set direct-estimation framework of a general theory of multitarget tracking which overcome the limitation of the traditional framework. Under this new framework, recent developments of the random set tracking techniques is discussed, in an attempt to explore further applications of random set theory to data fusion
Keywords :
estimation theory; random processes; sensor fusion; set theory; target tracking; data fusion; indirect-estimation tracking algorithms; multitarget tracking framework; random set theory; Filtering; Filters; Hidden Markov models; Kinematics; Position measurement; Set theory; State estimation; Surveillance; Target tracking; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on
Conference_Location :
Harbin
Print_ISBN :
0-7803-9395-3
Type :
conf
DOI :
10.1109/ISSCAA.2006.1627492
Filename :
1627492
Link To Document :
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