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中文摘要：
为了解决粒子滤波算法中存在的严重的退化现象,以及采用常规的重采样方法解决退化问题导致的粒子耗尽问题,研究了粒子滤波退化现象存在的原因和量子遗传算法具有的优点,将量子遗传算法引入粒子滤波,提出了基于量子遗传粒子滤波的无线传感器网络目标跟踪算法。通过量子遗传算法的编码方式增加粒子集的多样性,从而缓解了粒子滤波的退化现象并解决了粒子耗尽问题,而量子的并行性也节省了计算时间,提高了跟踪的实时性。仿真结果表明了该算法是可行的。
英文摘要：
Degeneracy phenomenon is serious in particle filter algorithm,common re-sampling method can resolve degeneracy phenomenon, but the sample impoverishment is a secondary result.To solve above problem,the causes of Particle filter degradation phenomena and the advantages of quantum genetic algorithm are studied.Tracking algorithms based on quantum genetic particle filter for wireless sensor networks is proposed,inwhich quantumgenetic algorithmis introduced.The diversity of particle sets increase through encoding of the quantum genetic algorithm,thus,the degradation in particle filter is eased and the problem of particle depletion is solved.Quantum parallelism saves the computation time and improved the real-time of tracking.Simulation results show the feasibility of the proposed algorithm.
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