Maximum-likelihood CFAR for Weibull background

Abstract

A low-loss CFAR algorithm for Weibull background is discussed. The two parameters (shape and scale) of the background statistics are estimated using a maximum-likelihood algorithm. A CFAR threshold based on parameters estimated in this way exhibits a smaller variance, and hence a smaller CFAR loss, than thresholds based on other estimation algorithms such as moments or order statistics. The analysis covers both complete and censored background sample sets.