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《Opto-Electronic Engineering》 2010-10
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Particle Filter Tracking Algorithm Based on Genetic Algorithm

CHEN Shan-jing1, 2a,YANG Hua1, 2a,ZENG Kai1, 2a,ZHANG Hong2b,WANG Yi-cheng2a ( 1. State Key Laboratory of Pulsed Power Laser Technology, Hefei 230037, China; 2. a. Key Lab of Infrared and Low Temperature Plasma of Anhui Province; b. Physics Staff Room, Electronic Engineering Institute, Hefei 230037, China )  
To solve the problem of particle degradation in particle filter tracking algorithm, the improved genetic algorithm is used in the particle re-sampling to improve the diversity of the sample. In the improved genetic algorithm, multinomial re-sampling is applied in selection and copy. An exchange rate of sample is a random number in given interval in cross-breeding. The Markov chain Monte Carlo move plus Gaussian white noise is used in sample variance and breeding, and the MH sampling algorithm is used to select sample, too. The improved particle filter tracking algorithm not only keeps the high efficient operation, but also improves stability of target tracking. Experimental results show that particle filter tracking algorithm is more stable and more accurate than traditional particle filter tracking algorithm.
【Fund】: 国家863高技术计划资助项目(2006AAJ103)
【CateGory Index】: TP391.41
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【Citations】
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