Year of Publication
Master of Science in Electrical Engineering (MSEE)
Dr. Kevin D. Donohue
Constant False Alarm Rate (CFAR) Processors are important for applications where thousands of detection tests are made per second, such as in radar. This thesis introduces a new method for CFAR threshold estimation that is particularly applicable to sound source detection with distributed microphone systems. The novel CFAR Processor exploits the near symmetry about 0 for the acoustic pixel values created by steered-response coherent power in conjunction with a partial whitening preprocessor to estimate thresholds for positive values, which represent potential targets.
To remove the low frequency components responsible for degrading CFAR performance, fixed and adaptive high-pass filters are applied. A relation is proposed and it tested the minimum high-pass cut-off frequency and the microphone geometry.
Experimental results for linear, perimeter and planar arrays illustrate that for desired false alarm (FA) probabilities ranging from 10-1 and 10-6, a good CFAR performance can be achieved by modeling the coherent power with Chi-square and Weibull distributions and the ratio of desired over experimental FA probabilities can be limited within an order of magnitude.
Saghaian Nejad Esfahani, Sayed Mahdi, "STATISTICAL MODELS FOR CONSTANT FALSE-ALARM RATE THRESHOLD ESTIMATION IN SOUND SOURCE DETECTION SYSTEMS" (2010). University of Kentucky Master's Theses. 46.