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Technical Program

Paper Detail

Paper:	SPTM-P2.4
Session:	Detection
Time:	Tuesday, May 16, 14:00 - 16:00
Presentation:	Poster
Topic:	Signal Processing Theory and Methods: Detection, Estimation, Classification Theory and Applications
Title:	GLRT-Based Direction Detectors in Noise and Subspace Interference
Authors:	Francesco Bandiera, Universitá degli Studi di Lecce, Italy; Olivier Besson, ENSICA, France; Danilo Orlando, Giuseppe Ricci, Universitá degli Studi di Lecce, Italy; Louis L. Scharf, Colorado State University, United States
Abstract:	In this paper we propose decision schemes to distinguish between the H_0 hypothesis that range cells under test contain disturbance only (i.e., noise plus interference) and the H_1 hypothesis that they also contain signal components along a direction which is a priori unknown, but constrained to belong to a given subspace of the observables. The disturbance is modeled in terms of complex normal noise vectors plus deterministic interference assumed to belong to a known subspace of the observables. At the design stage we resort to either the plain Generalized Likelihood Ratio Test (GLRT) or the two-step GLRT-based design procedure. Moreover, we assume that a set of noise only (secondary) data is available. A preliminary performance analysis, conducted by resorting to simulated data, shows that the one-step GLRT performs better than the two-step GLRT-based design procedure.