Title :
An ANN approach to multisensor multitarget tracking
Author :
Qiu, Bensheng ; Zhang, Diancheng
Author_Institution :
Hefei Univ. of Technol., China
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;
Conference_Titel :
Industrial Technology, 1994., Proceedings of the IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
0-7803-1978-8
DOI :
10.1109/ICIT.1994.467085
