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 〈H〉 of the observables. The disturbance is modeled in terms of complex normal noise vectors plus deterministic interference assumed to belong to a known subspace 〈J〉 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.
GLRT-Based Direction Detectors in Noise and Subspace Interference
BANDIERA, Francesco;RICCI, Giuseppe;
2006-01-01
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 〈H〉 of the observables. The disturbance is modeled in terms of complex normal noise vectors plus deterministic interference assumed to belong to a known subspace 〈J〉 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
