Abstract
A passive detection scheme based on information geometry is tested on underwater acoustic field data acquired through multiple sensors from the Distributed Network Consensus experiment. These detectors use a signal discovery method wherein a target is detected when the statistics of that signal are sufficiently different from those in a broadband background. The signal excess is viewed here as the non-Euclidean distance between two probability distributions interpreted as points in a Riemannian manifold. The SNR is artificially lowered to create a low SNR scenario and it is shown that in spite of this, the geometric detectors perform quite well.
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