Adaptive sidelobe blanker: a novel method of performance evaluation and threshold setting in the presence of inhomogeneous clutter

Abstract

The adaptive sidelobe blanker (ASB) detection algorithm consists of a cascade of two detectors: an adaptive matched filter (AMF) followed by an adaptive coherence estimator (ACE). The ASB has been shown to be effective at mitigating false alarms due to the presence of clutter inhomogeneities. This paper addresses two issues: how to choose thresholds for the component AMF and ACE detection algorithms, and how to predict the performance of the ASB in the presence of a given amount of clutter inhomogeneity, for which no general analytic closed-form solution exists. Two proposed methods of threshold choice aid the system designer in quantifying the losses that are incurred by use of the ASB.