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《Electronics Optics & Control》 2010-03
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Application of Genetic Fuzzy Clustering Algorithm in Data Association

HU Ao,FENG Xinxi,WANG Dongxu,GUO Weiwu (Institute of Telecommunication Engineering,Air Force Engineering University,Xi'an 710077,China)  
Traditional data association algorithm has the drawbacks of large computation cost and low association precision.To solve the problem,we proposed a genetic fuzzy clustering based data association algorithm.Taking the multi-target,multi-sensor data association as a combination optimization problem under a type of restrictions,fuzzy clustering were made for the measurement data of different sensors at the synchronized instant according to their similarity,and then the clustered equivalent measurement was used to estimate the state of each target.The improvement of clustering can strengthen the algorithm's local optimization capability and reduce the computation complexity considerably while eliminating some outliers.The simulation results show that the presented algorithm has high association precision and acceptable computational complexity,thus is practically valuable.
【Fund】: 军队科研基金资助项目(kj06104)
【CateGory Index】: V271.4
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