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Energy Confirmable Overlapping Target Tracking Based on Compressive Sensing in Wireless Sensor Networks
Juan Luo, Zanyi He, Yu Liu, Junli Zha and Keqin Li

Localization is highly critical for wireless sensor network applications. The present paper makes the following noticeable contributions. First, an energy confirmable overlapping tracking algorithm for mobile targets is proposed in wireless sensor networks. Different from most target localization algorithms based on compressive sensing, it improves localization accuracy through overlapping area and predicting regions in online tracking phase. Second, theoretical analyses suggest that grids number in an overlapping area is related to energy consumption. By exploiting a common communication schedule, we derive the compressive sensing tracking for the solution and formulate the threshold of grids number and the energy consumption. Third, our algorithm shows good scalability. Since only the network topology information around the unknown nodes is used, it can be applied to large-scale wireless sensor networks. Finally, analytical studies and simulations are provided to show that our proposed approach achieves significant tracking accuracy in four different trajectories.

Keywords: Compressive sensing, energy-efficient, tracking, wireless sensor networks

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