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

The authors present a thorough performance analysis of two covariance matri x estimators, the sample covariance matrix estimator (SCME) and the normali sed SCME (NSCME), which are employed by adaptive radar detectors in Gaussia n and compound-Gaussian clutter. Theoretical performance predictions are de rived, compared with the modified Cramer-Rao lower bound and checked with r eal-life sea clutter data. The results of the analysis show that the NSCME has superior performance in compound-Gaussian clutter and its performance i s insensitive to the clutter multivariate distribution within the range cel l under test and to the shape of the clutter correlation among different ra nge cells. Conversely, the performance of the SCME heavily depends on the c lutter distribution and has a dramatic worsening in spiky non-Gaussian clut ter.