BIPARAMETRIC CFAR PROCEDURES FOR LOGNORMAL CLUTTER

We consider procedures for constant false alarm rate in Lognormal clut ter, accounting for variations of both a scale and a shape parameter o f the clutter. Adaptivity to both parameters is obtained through bipar ametric estimation based on a sliding window surrounding the radar cel l under test We present some new procedures exploiting best linear unb iased estimation (BLUE) and compare them to a previous procedure calle d Log-t which uses maximum likelihood estimation. The comparison is ca rried on under homogeneous clutter environment and under instances of inhomogeneous environment (clutter edges and spurious targets). In the latter instances, some advantages of BLUE procedures are highlighted which stem from the opportunity of censoring.