Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Constant False Alarm Rate Sound Source Detection with Distributed Microphones | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2011 Article ID 656494 12 pages doi 2011 656494 Research Article Constant False Alarm Rate Sound Source Detection with Distributed Microphones Kevin D. Donohue Sayed M. SaghaianNejadEsfahani and Jingjing Yu Department of Electrical and Computer Engineering University of Kentucky Lexington KY 40506 USA Correspondence should be addressed to Kevin D. Donohue donohue@ Received 5 March 2010 Accepted 24 January 2011 Academic Editor Sven Nordholm Copyright 2011 Kevin D. Donohue et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 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. 1. Introduction Automatic sound source detection with distributed .
