一种应用于二进制传感器网络的目标跟踪算法

针对采用集中式粒子滤波方法解决二进制传感器网络目标跟踪问题存在的实时性较差和网络能量消耗大的缺点，提出了一种基于动态分簇的分布式粒子滤波算法。以随着目标运动而动态变化的簇为信息处理结构，簇头节点收集簇成员的单跳测量信息，实时对目标状态进行估计，非簇内节点进入休眠状态以节省能量。仿真表明，合理设置簇转换距离和激活半径，算法的跟踪精度与集中式粒子滤波方法相当；在不影响跟踪效果的情况下，可适当减小簇转换距离和激活半径，从而节省网络能量。

Target tracking algorithm applied in binary sensor networks

As adopting the central particle filter to solve the target tracking problem in binary sensor networks cannot do well in timeliness and energy conserving, a distributed particle filter based on dynamic clustering is proposed. The dynamic cluster is an information processing structure changing with the target’s movement, in which the cluster head collects the measurements from the cluster members through one hop communication and estimates the target states in real time; the other sensor nodes out of the cluster are turned into the sleep mode to save energy. Simulations indicate that when the cluster switching distance and the activation radius are properly set, the algorithm can have as a good tracking precision as the central particle filter. Besides, reducing the cluster switching distance and the activation radius will benefit the energy conserving for the network while does not affect the tracking effectiveness.