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This paper investigates the problem of generalized direction detection in unknown Gaussian noise in sample-starved environment where the training data are insufficient such that the original sample covariance matrix is singular. To devise effective detectors, we first perform a unitary matrix transformation to the test data, which results in a signal-free data set, denoted as the virtual training...
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