A parametric approach to hot clutter cancellation

Many reduced dimension STAP algorithms have been developed for airborne radar applications which rely on a stationary Doppler component of the interference in order to maintain acceptableper-formance. Two cases where this assumption is violated are when the gmund clutter contains intrinsic clutter motion (ICM) and when hot clutter is present. In addition to the non-stationa y Doppler component, hot clutter contains non-zem correlations in fast-time (across range bins) as well. This paper will present an algorithm designed to mitigate both gmund clutter and hot clutter in the same step using a two dimensional vector airtoregressive model to whiten the data in.space, fast-time, and slow-time. This is an extension of the Space-lime AutoRegwssive (STAR) filter that we have previously proposed. Using a simulated data set for circular array STAP augmented with synthetic hot clutter; we demonstrate that the extensions we present do result in a signiJ5cant perfor-mance increase over the standard STARJilter: In addition we also show that the STARjilters have a narmwer clutter notch than the optimized pre-Dopplerfilter when a finite sample support is used to train thefilters. 1