航空学报 > 2010, Vol. 31 Issue (9): 1849-1857

基于混合滤波的无线传感器网络融合跟踪方法

李峰荣, 刘贵喜, 孙庆方   

  1. 西安电子科技大学 机电工程学院
  • 收稿日期:2009-10-12 修回日期:2010-01-07 出版日期:2010-09-25 发布日期:2010-09-25
  • 通讯作者: 刘贵喜

A Fusion-tracking Scheme in Wireless Sensor Networks Based on Mixed Filtering

Li Fengrong, Liu Guixi, Sun Qingfang   

  1. School of Electronical and Machanical Engineering, Xidian University
  • Received:2009-10-12 Revised:2010-01-07 Online:2010-09-25 Published:2010-09-25
  • Contact: Liu Guixi

摘要: 针对无线传感器网络(WSN)中的多传感器融合目标跟踪,提出一种混合滤波算法,称为无迹混合集中式粒子滤波(UMCPF)。该算法使用了一个混合的粒子传播方案。在使用集中式粒子滤波(CPF)对WSN中的节点测量信息进行融合时,粒子滤波器中的一部分粒子使用从无迹变换(UT)获得的高斯分布作为建议分布进行粒子传播,而剩余的另一部分粒子则简单地使用状态转移先验分布进行粒子传播。WSN中的融合跟踪仿真结果表明,和纯粒子滤波算法CPF相比,在仿真速率相当的情况下,混合滤波算法明显提高了跟踪精度和稳定性。

关键词: 无线传感器网络, 目标跟踪, 粒子滤波, 多传感器融合, 混合滤波

Abstract: This article proposes an unscented-mixed centralized particle filter (UM-CPF) to deal with multi-sensor fusion based target tracking applications in wireless sensor networks (WSNs). The algorithm utilizes a mixed particle-propagation scheme. In the process of multi-sensor measurement fusion using a centralized particle filter (CPF) in WSN, a certain number of particles in the CPF are propagated by using a Gaussian distribution obtained from an unscented transformation (UT) as the proposal distribution, while the rest of the particles are simply propagated by using the state transition prior distribution. Simulation results of fusion-tracking in WSN show that, with a similar simulation speed, the mixed filter significantly increases the tracking accuracy and robustness as compared with the results obtained by the pure CPF.

Key words: wireless sensor network, target tracking, particle filter, multisensor fusion, mixed filtering

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