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Improved particle filtering techniques based on generalized interactive genetic algorithm 被引量:4
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作者 Yan Zhang Shafei Wang Jicheng Li 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第1期242-250,共9页
This paper improves the resampling step of particle filtering(PF) based on a broad interactive genetic algorithm to resolve particle degeneration and particle shortage.For target tracking in image processing,this pa... This paper improves the resampling step of particle filtering(PF) based on a broad interactive genetic algorithm to resolve particle degeneration and particle shortage.For target tracking in image processing,this paper uses the information coming from the particles of the previous fame image and new observation data to self-adaptively determine the selecting range of particles in current fame image.The improved selecting operator with jam gene is used to ensure the diversity of particles in mathematics,and the absolute arithmetical crossing operator whose feasible solution space being close about crossing operation,and non-uniform mutation operator is used to capture all kinds of mutation in this paper.The result of simulating experiment shows that the algorithm of this paper has better iterative estimating capability than extended Kalman filtering(EKF),PF,regularized partide filtering(RPF),and genetic algorithm(GA)-PF. 展开更多
关键词 particle filtering(PF) particle degeneration particle shortage broad interactive genetic algorithm
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