Matched subspace detectors
Date
1994
Authors
Friedlander, Benjamin, author
Scharf, Louis L., author
IEEE, publisher
Journal Title
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Volume Title
Abstract
In this paper we formulate a general class of problems for detecting subspace signals in subspace interference and broadband noise. We derive the generalized likelihood ratio (GLR) for each problem in the class. We then establish the invariances for the GLR and argue that these are the natural invariances for the problem. In each case, the GLR is a maximal invariant statistic, and the distribution of the maximal invariant statistic is monotone. This means that the GLR test (GLRT) is the uniformly most powerful invariant detector. We illustrate the utility of this finding by solving a number of problems for detecting subspace signals in subspace interference and broadband noise. In each case we give the distribution for the detector and compute performance curves.
Description
Rights Access
Subject
matched filters
linear algebra
filtering and prediction theory
electromagnetic interference
noise
signal detection