Robust detection of signals in dependent noise

The robust detection of signals in additive dependent noise is considered. The solution to the finite-sample problem is obtained when the Bayes risk is used as the performance measure. For the multivariate densities involved we assume that they belong to an e-contamination model. The robust detection structure is shown to be optimum for the least-favorable density and is a censored version of the nominal likelihood ratio.