基于动态分簇路由优化和分布式粒子滤波的传感器网络目标跟踪方法

针对无线传感器网络中节点通信能力及能量有限的情况,该文提出基于动态分簇路由优化和分布式粒子滤波的传感器网络目标跟踪方法。该方法以动态分簇的方式将监测区域内随机部署的传感器节点划分为若干个簇,并对簇内成员节点与簇首节点之间、簇首节点与基站之间的通信路由进行优化,确保网络能耗的均衡分布,在此基础上,被激活的簇内成员节点并行地执行分布式粒子滤波算法实现目标跟踪。仿真结果表明,该方法能有效地降低传感器网络中节点的总能耗,能在实现跟踪的同时保证目标跟踪的精度。

Target Tracking Algorithm for Wireless Sensor Networks Based on Dynamic Cluster Routing Optimization and Distributed Particle Filter

Due to the limited communication capability and energy constraint of sensor nodes,a target tracking scheme is proposed for sensor networks based on Dynamic Cluster Routing Optimization and Distributed Particle Filter(DCRO-DPF).In order to achieve a balanced distribution of network energy consumption,DCRO-DPF utilizes a dynamic clustering approach to divide the nodes which deployed randomly in the monitored region into a number of clusters,then optimizes not only the communication routes between member nodes and cluster head in each cluster,but also the communication routes between cluster heads and the base station.On this basis,the activated cluster member nodes execute distributed particle filter to track the maneuvering target.The simulations corroborate that this scheme can effectively reduce the total energy consumption of the sensor networks,achieve the goal of tracking and guarantee the tracking accuracy simultaneously.