  We address adaptive radar detection of targets embedded in ground clutter
dominated environments characterized by a symmetrically structured power
spectral density. At the design stage, we leverage on the spectrum symmetry for
the interference to come up with decision schemes capable of capitalizing the
a-priori information on the covariance structure. To this end, we prove that
the detection problem at hand can be formulated in terms of real variables and,
then, we apply design procedures relying on the GLRT, the Rao test, and the
Wald test. Specifically, the estimates of the unknown parameters under the
target presence hypothesis are obtained through an iterative optimization
algorithm whose convergence and quality guarantee is thoroughly proved. The
performance analysis, both on simulated and on real radar data, confirms the
superiority of the considered architectures over their conventional
counterparts which do not take advantage of the clutter spectral symmetry.
