Abstract
Due to significant advancements in embedded systems, sensor devices and wireless communication technology, sensor networks have been attracting widespread attention in areas such as target tracking, monitoring, and surveillance. Technological advancements made it possible to deploy a large number of inexpensive but technically advanced sensors to cover wide areas. However, when a tracking system has to track a large number of targets, the computation and communication loads arise. In this paper we propose a task assignment algorithm based on linear matrix inequalities (LMI) to reduce the computational complexity and communication load. Simulation results and a comparison with the Kalman filtering strategy confirm the suitability of the approach.
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