McWhorter, L. Todd, authorScharf, Louis L., authorKraut, Shawn, authorIEEE, publisher2007-01-032007-01-032001Kraut, Shawn, Louis L. Scharf, and L. Todd McWhorter, Adaptive Subspace Detectors, IEEE Transactions on Signal Processing 49, no. 1 (January 2001): 1-16.http://hdl.handle.net/10217/752In this paper, we use the theory of generalized likelihood ratio tests (GLRTs) to adapt the matched subspace detectors (MSDs) of [1] and [2] to unknown noise covariance matrices. In so doing, we produce adaptive MSDs that may be applied to signal detection for radar, sonar, and data communication. We call the resulting detectors adaptive subspace detectors (ASDs). These include Kelly's GLRT and the adaptive cosine estimator (ACE) of [6] and [19] for scenarios in which the scaling of the test data may deviate from that of the training data. We then present a unified analysis of the statistical behavior of the entire class of ASDs, obtaining statistically identical decompositions in which each ASD is simply decomposed into the nonadaptive matched filter, the nonadaptive cosine or t-statistic, and three other statistically independent random variables that account for the performance-degrading effects of limited training data.born digitalarticleseng©2001 IEEE.Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.matched subspace detectordata communicationadaptive subspace detectoradaptive signal detectionradar detectionsonar detectionText