The constant false alarm rate (CFAR) matched subspace detector (CFAR MSD) i
s 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, Recently, the CFAR adaptive
subspace detector (CFAR ASD), or adaptive coherence estimator (ACE), was pr
oposed for detecting a target signal in noise whose covariance structure an
d level are both unknown and whose covariance structure is estimated with a
sample covariance matrix based on training data. We show here that the CFA
R 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.