Adaptive strategies for discrimination between mainlobe and sidelobe signals

Abstract

We address adaptive discrimination between the signal of interest and a sidelobe interferer. To this end, we propose a detector derived resorting to a GLRT implementation of the generalized Neyman-Pearson rule and a two-stage detection scheme. The adaptive detectors rely on secondary data, free of signal components, but sharing the statistical characterization of the noise in the cell under test, in order to guarantee the CFAR property.