Asymptotically robust detection using statistical moments

While locally optimum detection requires complete knowledge of the noise density, we use only the first few absolute moments of the independent, identically distributed (iid) noise to obtain a robust detector that is locally optimum for the least favorable noise satisfying these moments. This robust detector´s efficacy approaches that of the asymptotically optimum detector, while requiring limited knowledge of the noise statistics