A polarimetric adaptive matched filter

In this paper, we address polarimetric adaptive detection of targets embedded in Gaussian noise with unknown covariance matrix. To this end we assume that a set of secondary data, free of signal components and with the same covariance matrix of the cell under test, is available. We resort to a two-step design procedure based upon the generalized likelihood ratio test (GLRT). It is shown that the newly proposed detector has the constant false alarm rate property with respect to the covariance matrix of the noise. More remarkably, it has the same performance, but a lower complexity, than the corresponding plain GLRT. (C) 2001 Elsevier Science B.V. All rights reserved