Information content-based sensor selection for collaborative target tracking

An energy-efficient collaborative target tracking paradigm is developed for wireless sensor networks (WSNs). The network lifetime is prolonged by selecting a subset of sensors that are informative and provide non-redundant data so that a desired accuracy level is maintained. A distributed data fusion architecture provides the collaborative tracking framework. A mutual information-based sensor selection algorithm (MISS) is adopted for participation in the fusion process. MISS allows the most informative subset of the sensors to transmit data so that in the energy consumption is reduced while the desired accuracies of the target position estimation are preserved. Simulation results that demonstrate the performance improvement offered by the MISS algorithm are also furnished.