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.