Diffuse field estimation with asynchronous sensor networks

Sensor networks provide a convenient way of estimating diffuse fields, but deployment issues and inaccurate clock synchronization may introduce randomness in their behavior. Recently, asynchronous sensor networks (ASN) comprising uncoordinated and randomly placed nodes, have been shown to sustain quasi-stable communication. In order to conserve energy, it is desirable to reduce the number of samples to a minimum. The theory of compressive sensing offers methods of recovering sparse signals from a small set of random measurements. We show that the random space-time sampling in an ASN provides the additional advantage of satisfying the properties required for compressive sensing.