量子遗传优化粒子滤波的WSN目标跟踪算法  

Wireless Sensor Networks Target Tracking Based on Particle Filtering Optimized by Quantum Genetic Algorithm

作　　者：董跃钧[1] 李国伟[1] 

机构地区：[1]中原工学院计算机学院,郑州450000

出　　处：《科学技术与工程》2013年第12期3305-3309,共5页Science Technology and Engineering

基　　金：河南省科技基金(102102210508)资助

摘　　要：在无线传感器网络(WSN)目标跟踪应用中,传统粒子滤波算法存在多样性退化问题。为提高WSN目标跟踪精度,提出一种基于量子遗传算法优化粒子滤波的WSN目标跟踪方法。量子遗传算法不仅增加粒子多样性,防止粒子退化现象出现,有效缩短了计算时间且改善粒子跟踪能力。测试结果表明,所提出算法很好地减轻了粒子退化对目标跟踪精度影响,提高了WSN目标跟踪精度和跟踪的实时性,跟踪结果令人满意。In order to solve the problem of the diversity of particles degradation, improving wireless sensor net- work （WSN） target tracking accuracy, a target tracking method based on particle filter optimized by quantum ge- netic algorithm is proposed. Quantum genetic algorithm not only increases the diversity of particles to prevent the particle degeneracy phenomenon, and improves the estimation, tracking ability and effectively shortens the calcula- tion time. The simulation results show that the proposed algorithm is very good, reduced particle degradation on the target tracking accuracy, improves the WSN target tracking accuracy and real-time tracking, the tracking results is satisfactory.

关 键 词：无线传感器网络 目标跟踪 粒子滤波 量子遗传算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]