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Application of Particle Filter for Target Tracking in Wireless Sensor Networks

机译:粒子滤波器在无线传感器网络中的目标跟踪中的应用

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In the application of particle filter algorithm for target tracking in wireless sensor networks, an Auxiliary particle filter (APF) and Gaussian particle filter (GPF) are discussed to solve the particle degradation problem of Particle Filter (PF). By introducing an auxiliary variable and two rounds weighted processes, APF makes the particle weights stable and relaxies particle degradation. GPF uses a Gaussian density function to approximately estimate posterior probability distribution. It doesn't require re-sampling, and there is no particle degradation. Therefore, three algorithm are applied to single-target tracking in wireless sensor networks. Finally, the comparison of three algorithm's performance in target tracking is presented and the simulation results are also given. From these results we can see that APF has better accuracy than PF algorithm and GPF has better accuracy and real-time performance than PF algorithm.
机译:在无线传感器网络中的目标跟踪粒子滤波器算法的应用中,讨论了辅助粒子滤波器(APF)和高斯粒子滤波器(GPF)以解决颗粒滤波器(PF)的颗粒劣化问题。 通过引入辅助变量和两个轮加权过程,APF使粒子重量稳定并且松弛颗粒劣化。 GPF使用高斯密度函数以近似估计后验概率分布。 它不需要重新采样,没有颗粒劣化。 因此,在无线传感器网络中应用了三种算法在单目标跟踪中。 最后,提出了三种算法在目标跟踪中的性能的比较,并且还给出了模拟结果。 根据这些结果,我们可以看到APF具有比PF算法更好的精度,而GPF具有比PF算法更好的准确性和实时性能。

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