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Matched subspace detectors

IEEE Transactions on Signal Processing · 1994 · Vol. 42(8) · pp. 2146–2157
Louis L. ScharfB. Friedlander

Abstract

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.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Radar Systems and Signal ProcessingImage and Signal Denoising MethodsDirection-of-Arrival Estimation TechniquesSubspace topologyMathematicsDetectorInvariant (physics)Test statisticMonotone polygonInvariant subspaceAlgorithmStatisticDetection theory

Funding

  • National Science Foundation
  • Office of Naval Research
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937
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