基于量子遗传粒子滤波的无线传感器网络的目标跟踪算法的研究

Research on Target Tracking Algorithm of Wireless Sensor Networks Based on Quantum Genetic Particle Filter

摘要:

摘要： 文章主要研究的是关于量子遗传粒子滤波跟踪算法，应用量子遗传算法有效保证粒子组成的多样性，从而减缓了粒子滤波的退化现象，解决了粒子耗尽问题。本文通过引入量子的概念，同时让其并行可以有效地减少算法的运行时间，实时跟踪性能得到了大大提高。通过仿真结果表明该算法具有有效性、可行性。通过仿真：与原算法相比，在大噪声条件下量子遗传粒子滤波算法改善了粒子贫乏问题，提高了跟踪精度。

Abstract:

Abstract : A quantum genetic particle filter tracking algorithm is proposed in this paper. Quantum genetic algorithm (QGA) is used to increase the diversity of the particle set, so as to alleviate the degradation of particle filter and solve the problem of particle depletion. Quantum parallelism also saves computing time and improves the real-time performance of tracking. The simulation results show that the algorithm is feasible. The simulation results show that compared with the original algorithm, the quantum genetic particle filter algorithm can improve the particle impoverishment problem and the tracking accuracy under the condition of large noise.