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.