Adaptive Detection Using Whitened Data When Some of the Training Samples Undergo Covariance Mismatch

We consider adaptive detection of a signal of interest when two sets of training samples are available, one sharing the same covariance matrix as the data under test, the other set being mismatched. The approach proposed in this letter is to whiten both the data under test and the matched training samples using the sample covariance matrix of the mismatched training samples. The distribution of the whitened data is then derived and subsequently the generalized likelihood ratio test is obtained. Numerical simulations show that it performs well and is rather robust.