Performance analysis of two covariance matrix estimators in compound-Gaussian clutter

The authors present a thorough performance analysis of two covariance matrix estimators, the sample covariance matrix estimator (SCME) and the normalised SCME (NSCME), which are employed by adaptive radar detectors in Gaussian and compound-Gaussian clutter. Theoretical performance predictions are derived, compared with the modified Cramer-Rao lower bound and checked with real-life sea clutter data. The results of the analysis show that the NSCME has superior performance in compound-Gaussian clutter and its performance is insensitive to the clutter multivariate distribution within the range cell under test and to the shape of the clutter correlation among different range cells. Conversely, the performance of the SCME heavily depends on the clutter distribution and has a dramatic worsening in spiky non-Gaussian clutter.