Matched subspace detectors generalize the matched filter by accommodating signals that are only constrained to lie in a multidimensional subspace. There are four of these detectors, depending upon knowledge of signal phase and noise power. The adaptive subspace detectors generalize the matched subspace detectors by accommodating problems where the noise covariance matrix is unknow, and must be estimated from training data. In this paper we review the geometries and invariances of the matched and adaptive subspace detectors. We also establish that every version of a matched or adaptative subspace detectors can be interpreted as an estimator of output signal-to-noise ratio (SNR), in disquise
