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Exploiting Spatial Correlation for Improving Coverage in Sensor Networks

This paper investigates the benefits of spatial correlation for the problem of coverage in Wireless Sensor Networks (WSN). Specifically, it studies two detectors, the Mean Detector (MD) and the Covariance Detector (CD) and compares their coverage performance for various scenarios. The main contribution of this paper is to show that one can exploit the possible correlation between measurements of neighboring sensor nodes in order to achieve significantly better coverage. Moreover, the results of this paper have direct implications on the topology of the network. Our results indicate that for the CD the best placement would be pairs of sensor nodes placed on a grid configuration.