An algorithm for detecting a random target signal against a mixture of corr
elated compound-Gaussian clutter and white Gaussian thermal noise is propos
ed. The new detection strategy is obtained by extending the generalised mat
ched subspace detector previously derived by Gini and Farina (1999) for onl
y compound-Gaussian clutter. Two different versions of the detection strate
gy are proposed and compared: the first relies on the estimation of the rad
ar clutter texture component; the second trades-off performance with comput
ational complexity by using the texture mean value in place of its estimate
. The texture estimator mean square error is derived in closed form and ana
lysed. Additionally, the robustness of the detector false alarm rate to cha
nges of clutter parameters and the detection performance are numerically in
vestigated by Monte Carlo simulation.