Robust Distributed Detection Using Low Power Acoustic Sensors

This paper describes a robust detection algorithm implemented on a network of acoustic sensors. The sensors are severely constrained in both power and computational performance. A variety of techniques are employed to extract maximum detection range while minimizing false alarm rates under these constraints. These include automatic gain control, background estimation and adaptive thresholding, and collaboration among distributed sensors for false alarm mitigation. The resulting algorithm is both robust and sufficiently general to be applied in a variety of sensor domains. The algorithm was implemented and deployed on prototype hardware and operated in real time under realistic operational conditions.