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This paper deals with the problem of testing the equality of M covariance matrices. We first identify a suitable group of transformations leaving the problem invariant and obtain the corresponding Maximal Invariant Statistic. Then, the Generalized Likelihood Ratio Test (GLRT) is recalled and explicit expressions for Rao, Wald, Gradient and Durbin tests are provided. Also, equivalences among them and with other well-known tests proposed in open literature (mostly for the realvalued case) are analyzed and compared. Finally, the application of the proposed framework to the relevant signal processing application of multi-pass Coherent Change Detection (CCD) in polarimetric Synthetic Aperture Radar (SAR) is demonstrated both on simulated and on live data.

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This page is a summary of: On Multiple Covariance Equality Testing with Application to SAR Change Detection, IEEE Transactions on Signal Processing, October 2017, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/tsp.2017.2712124.
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