Friedlander, Benjamin, authorScharf, Louis L., authorIEEE, publisher2007-01-032007-01-031994Scharf, Louis L. and Benjamin Friedlander, Matched Subspace Detectors, IEEE Transactions on Signal Processing 42, no. 8 (August 1994): 2146-2157.http://hdl.handle.net/10217/740In 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.born digitalarticleseng©1994 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 filterslinear algebrafiltering and prediction theoryelectromagnetic interferencenoisesignal detectionText