Matched Direction Detectors
Olivier Besson, Louis L. Scharf, François Vincent · 2006
In this paper, we address the problem of detecting a signal whose associated spatial signature is subject to uncertainties, in the presence of subspace interference and broadband noise, and using multiple snapshots from an array of sensors. To account for steering vector uncertainties, we assume that the spatial signature of interest lies in a given linear subspacewhile its coordinates in this subspace are unknown. The generalized likelihood ratio test (GLRT) for the problem at hand is formulated. We show that the GLRT amounts to searching for the best direction in the subspaceafter projecting out the interferences. The distribution of the GRLT under both hypotheses is derived and numerical simulations illustrate its performance.