Analysis of order-statistic CFAR threshold estimators for improved ultrasonic flaw detection

In the pulse-echo method using broadband transducers, flaw detection can be improved by using optimal bandpass filtering to resolve flaw echoes surrounded by grain scatterers. Optimal bandpass filtering is achieved by examining spectral information of the flaw and grain echoes where frequency differences have been experimentally shown to be predictable in the Rayleigh scattering region. Using optimal frequency band information, flaw echoes can then be discriminated by applying adaptive thresholding techniques based on surrounding range cells. The authors present order-statistic (OS) processors, ranked and trimmed mean (TM), to robustly estimate the threshold while censoring outliers. The design of these OS processors is accomplished analytically based on constant false-alarm rate (CFAR) detection. It is shown that OS-CFAR and TM-CFAR processors can detect flaw echoes robustly with the CFAR of 10 (-4) where the range cell used for the threshold estimate contains outliers.