DocumentCode
3351046
Title
An ANN approach to multisensor multitarget tracking
Author
Qiu, Bensheng ; Zhang, Diancheng
Author_Institution
Hefei Univ. of Technol., China
fYear
1994
fDate
5-9 Dec 1994
Firstpage
410
Lastpage
413
Abstract
In this paper, the multisensor multitarget tracking problem is considered. The data association is most important and difficult in the multitarget tracking environment. We first formulate it with the maximum likelihood method, and then we use a random stochastic ANN and modified mean field annealing to solve the optimal solution. Compared with other nonlinear optimization algorithms, this method can achieve the global optimal solution and it needs fewer iteration times
Keywords
maximum likelihood detection; neural nets; sensor fusion; simulated annealing; target tracking; tracking; data association; global optimal solution; maximum likelihood method; mean field annealing; multisensor multitarget tracking; random stochastic neural nets; Annealing; Artificial intelligence; Direction of arrival estimation; Maximum likelihood estimation; Optimization methods; Radar tracking; Sonar; State estimation; Stochastic processes; Target tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Technology, 1994., Proceedings of the IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
0-7803-1978-8
Type
conf
DOI
10.1109/ICIT.1994.467085
Filename
467085
Link To Document