Abstract
Distributed targets detection in Gaussian noise is studied. Since the noise power is possible to change from cell to cell due to the heterogeneity of the surveillance area, the noise in the test/training data is assumed to have the same structure of covariance matrix (CM) but various powers. Three detectors are derived via the generalized likelihood ratio test, Rao and Wald tests, respectively. The new detectors have the statistical constant false alarm rate (CFAR) properties against the noise power and structure of the noise CM. Monte Carlo simulations show that the new detectors outperform their counterparts.
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