无线传感器网络中的分布式目标被动跟踪算法  

Decentralized Algorithm for Target Passive Tracking in Wireless Sensor Networks

作　　者：薛锋[1] 刘忠[1] 曲毅[1] 

机构地区：[1]海军工程大学电子工程学院,湖北武汉430033

出　　处：《系统仿真学报》2007年第15期3499-3502,共4页Journal of System Simulation

基　　金："十一五"国防仿真预研基金(513040303)

摘　　要：为提高目标被动跟踪性能,并降低无线传感器网络(WSN)中的能量开销,提出了一种新的分布式信息粒子滤波(IPF)算法。根据目标的当前位置,将WSN中的结点动态组织成簇,建立分布式跟踪结构。利用信息扩展卡尔曼滤波器结合最新的观测量,产生粒子滤波的建议分布,详细推导了基于动态分簇结构的IPF具体实现步骤。建立机动目标跟踪的WSN仿真环境,比较了三种跟踪算法的性能和通信数据量。仿真结果表明,IPF具有较高的跟踪精度,与集中式粒子滤波算法的跟踪性能接近,而且降低了节点间的通信数据量。To improve the passive tracking performance and to reduce the energy cost in wireless sensor networks （WSN）, a new decentralized information particle-filtering （IPF） algorithm was proposed. Dynamic clusters were organized according to the current position of the target, and the decentralized tracking structure was constructed. The information extended Kalman filter was used to incorporate the newest observation into the proposal distribution of the IPF, and specific implementation steps of the IPF were deduced based on the dynamic clustering structure. Tracking simulations of maneuvering target were conducted, and tracking performances and communication costs of three algorithms were compared in this simulation environment. Simulation results show that the IPF has similar good performance in the tracking accuracy with the centralized particle filtering, and that the IPF reduces the communication cost between nodes during the tracking.

关 键 词：被动跟踪 分布式算法 无线传感器网络 信息滤波 粒子滤波 

分 类 号：TN953[电子电信—信号与信息处理]