Constant False Alarm Rate Sound Source Detection with Distributed Microphones

Abstract

Applications related to distributed microphone systems are typically initiated with sound source detection. This paper introduces a novel method for the automatic detection of sound sources in images created with steered response power (SRP) algorithms. The method exploits the near-symmetric coherent power noise distribution to estimate constant false-alarm rate (CFAR) thresholds. Analyses show that low-frequency source components degrade CFAR threshold performance due to increased nonsymmetry in the coherent power distribution. This degradation, however, can be offset by partial whitening or increasing differential path distances between the microphone pairs and the spatial locations of interest. Experimental recordings are used to assess CFAR performance subject to variations in source frequency content and partial whitening. Results for linear, perimeter, and planar microphone geometries demonstrate that experimental false-alarm probabilities for CFAR thresholds ranging from 10^-1 and 10^-6 are limited to within one order of magnitude when proper filtering, partial whitening, and noise model parameters are applied.

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