IEEE Transactions on Signal Processing · 1999 · 595 citations · 8 references
ComputingData ScienceMeasurement InvarianceStatistical LearningTime Series AnalysisMultigroup Measurement InvarianceSignal Detection TheoryCovariance Matrix EstimationCovariance StructureCovariance Structure AnalysisCovariance Structure ModelingMatched FilteringSubspace Learning
The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) is the uniformly most-powerful-invariant test and the generalized likelihood ratio test (GLRT) for detecting a target signal in noise whose covariance structure is known but whose level is unknown. Previously, the CFAR adaptive subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was proposed for detecting a target signal in noise whose covariance structure and level are both unknown and whose covariance structure is estimated with a sample covariance matrix based on training data. We show here that the CFAR ASD is GLRT when the test measurement is not constrained to have the same noise level as the training data, As a consequence, this GLRT is invariant to a more general scaling condition on the test and training data than the well-known GLRT of Kelly (1986).
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A CFAR adaptive matched filter detector
Frank C. Robey, Daniel R. Fuhrmann, Edward J. Kelly et al. · IEEE Transactions on Aerospace and Electronic Systems · 1992 · 1.6K citations
Louis L. Scharf, B. Friedlander · IEEE Transactions on Signal Processing · 1994 · 942 citations · Full text