中文摘要：

目标追踪是无线传感器网络的最重要的应用程序之一。优化计算和精力驱散是批评要求节省传感器节点的有限资源。追踪框架的一个新柔韧、精力有效的合作目标在这篇文章被建议。在一个目标被检测以后，仅仅一活跃的簇为追踪的任务在负责每次走。追踪的算法被传递从一簇察觉到和计算操作到另外一个散布。改革计划的事件驱动簇也为在节点之中平衡精力消费被建议。从成员们被选择的三簇和粒子的一个新班的观察过滤称为的费用参考粒子过滤器(CRPF ) 被介绍在簇头估计目标运动。这个 CRPF 方法为因为它掉知道系统进程和观察噪音的概率分布的强壮的假设，追踪应用程序的无线传感器网络是相当柔韧的。在模拟实验，追踪算法的建议合作目标的表演被追踪精确和网络精力消费的度量标准评估。

英文摘要：

Target tracking is one of the most important applications of wireless sensor networks. Optimized computation and energy dissipation are critical requirements to save the limited resource of sensor nodes. A new robust and energy-efficient collaborative target tracking framework is proposed in this article. After a target is detected, only one active cluster is responsible for the tracking task at each time step. The tracking algorithm is distributed by passing the sensing and computation operations from one cluster to another. An event-driven cluster reforming scheme is also proposed for balancing energy consumption among nodes. Observations from three cluster members are chosen and a new class of particle filter termed cost-reference particle filter （CRPF） is introduced to estimate the target motion at the cluster head. This CRPF method is quite robust for wireless sensor network tracking applications because it drops the strong assumptions of knowing the probability distributions of the system process and observation noises. In simulation experiments, the performance of the proposed collaborative target tracking algorithm is evaluated by the metrics of tracking precision and network energy consumption.