A compact distributed target tracking algorithm for binary wireless sensor networks

One of the important applications in sensor networks is target tracking. Usually it is difficult to balance the optimization goals of the tracking precision, computation cost and network communication traffic for target localization in a distributed manner. The binary sensing model is analyzed where individual sensor only returns the information regarding target's presence or absence within its sensing range. A cooperative distributed algorithm based on the triplet circle intersection principle is proposed for maneuvering target tracking by this kind of sensor network. The central point of a common intersection arc among sensor range circles is considered as the target estimation position through a compact computation manner. By combining data from neighboring sensors, this algorithm enables tracking with a resolution higher than that of the traditional average method. The triplet circle intersection model is applied to decrease the localization cost and communication traffic; therefore it fits low-power sensor networks. Simulation experimentations have been designed to verify the algorithm performance. A good tracking quality can be achieved to optimize comprehensive goals of precision, computation and traffic. Moreover, in the paper the conventional performance evaluation criterions about average error and root mean square error are improved to reflect the intrinsic measurement effectiveness of a target tracking problem in a more excellent way.