Target classification and localization in habitat monitoring

We are developing an acoustic habitat-monitoring sensor network that recognizes and locates specific animal calls in real time. In this paper, we investigate the system requirements of such a real-time acoustic monitoring network. We propose a system architecture and a set of lightweight collaborative signal processing algorithms that achieve real-time behavior while minimizing inter-node communication to extend the system lifetime. In particular, the target classification is based on spectrogram pattern matching while the target localization is based on beamforming using Time Difference Of Arrival (TDOA). We describe our preliminary implementation on a Commercial Off The Shelf (COTS) testbed and present its performance based on testbed measurements.