Collaborative Target Tracking in Wireless Sensor Networks
Xiaofei Xing, Guojin Wang and Jie Li
Target tracking is a killer application in wireless sensor networks. A lot of work has been done to improve the localization and tracking algorithms with smart sensors. However, achieving a high tracking accuracy with energy efficiency is challenging. In this paper, we propose a collaborative target tracking (CTT) scheme that enables accurate tracking with a binary detection model. In this scheme, all sensors in the monitoring field are divided into clusters using a clustering algorithm. This scheme consists of three parts: (i) A tracking node group near the target is first constructed when the distance weights of the sensors meet the requirements of tracking accuracy; (ii) A tracking group is updated dynamically with the moving of the target; (iii) A tracking group predicts the target trajectory and adjusts the frequency of data reporting according to the target’s velocity. Extensive simulation results show that our scheme achieves high performance in terms of tracking accuracy and energy efficiency under different settings.
Keywords: Wireless sensor networks, target tracking, energy efficiency, state transition.