DocumentCode :
3543191
Title :
An improved algorithm for maximum-likelihood based approach for a multitarget tracking problem
Author :
Chen, Liang ; Hua, Qiang ; Kwan, H.K.
Author_Institution :
Comput. Sci. Dept., Univ. of Northern British Columbia, Prince George, BC, Canada
fYear :
2005
fDate :
23-26 May 2005
Firstpage :
1421
Abstract :
It has been shown that the optimal solution for the matching problem in multi-target tracking, when both estimated measuring bearing data and actual measuring data are known, can be found from among N different matchings. This paper shows by experiment that the costs of the N different possible solutions constitute a bimodal sequence, which suggests an algorithm of O(N-logN) complexity for the matching, lower than most known algorithms. An improved algorithm for the whole process of the multi-target tracking problem is obtained, and an improved performance is shown.
Keywords :
direction-of-arrival estimation; maximum likelihood estimation; optimisation; target tracking; bearing data; bimodal sequence; complexity; matching problem; maximum-likelihood based approach; multitarget tracking; optimal solution; performance; Computer science; Costs; Electric variables measurement; Machine learning; Machine learning algorithms; Maximum likelihood estimation; Sensor arrays; Sensor systems; Target tracking; Time measurement; Data assignment problem; maximum likelihood principle; multiple target tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN :
0-7803-8834-8
Type :
conf
DOI :
10.1109/ISCAS.2005.1464864
Filename :
1464864
Link To Document :
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