Matched subspace detectors
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Authors
Friedlander, Benjamin, author
Scharf, Louis L., author
IEEE, publisher
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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.
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Rights Access
Subject
 matched filters 
 linear algebra 
 filtering and prediction theory 
 electromagnetic interference 
 noise 
 signal detection 
