On Localized Prediction for Power Efficient Object Tracking in Sensor Networks
ICDCSW '03 Proceedings of the 23rd International Conference on Distributed Computing Systems
Maximum likelihood methods for bearings-only target localization
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
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Energy is one of the critical constraints for the applications of sensor network. In the earlier target detection and tracking algorithm power saving is achieved by letting most of the non-border sensor nodes in the cluster stay in hibernation state. However, the border sensor nodes consume a significant amount of energy since they are supposed to be on all the time for target detection. In this paper we propose a new target detection scheme which lets the border sensor nodes be on shortly one after another in a circular fashion to minimize the energy consumption. Computer simulation shows that the proposed scheme can significantly reduce the energy consumption in target detection and tracking compared to the earlier scheme.