Title :
Data Association based on Chaotic Optimization Adaptive Genetic Algorithm
Author :
Zhu, Zhiyu ; Zhang, Bing
Author_Institution :
Dept. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., Zhenjiang
Abstract :
Through estimating the optimal corresponding relationship between measurements and dynamic states of targets, data association can be depicted as a kind of constrained combination optimization problem. Chaotic optimization adaptive genetic algorithm is applied to solve data association, the simulation results indicate that it has high successful association ratio; Furthermore, adaptive genetic algorithm, chaotic optimization algorithm and chaotic optimization adaptive genetic algorithm are respectively adopted to solve data association, as a result chaotic optimization adaptive genetic algorithm has better association ability than the other two algorithms, besides faster convergence speed.
Keywords :
chaos; combinatorial mathematics; genetic algorithms; sensor fusion; association ratio; chaotic optimization adaptive genetic algorithm; constrained combination optimization problem; data association; Chaos; Constraint optimization; Equations; Explosions; Genetic algorithms; Noise measurement; Optimization methods; State estimation; Systems engineering and theory; Target tracking; adaptive genetic algorithm; chaotic optimization; data association; multiple targets tracking;
Conference_Titel :
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location :
Beijing
Print_ISBN :
7-302-13922-9
Electronic_ISBN :
7-900718-14-1
DOI :
10.1109/CESA.2006.4281931