Asymptotically robust detection for known signals in contaminated multiplicative noise

Abstract Robust detection of known weak signals of unknown amplitude is considered for a class of combined additive and nonadditive noise models and an asymptotically large set of independent observations. Cases where the additive noise distribution is known only to be a member of the Tukey-Huber contamination class of symmetric distributions and cases where the observation model is also known only to be a member of a particular class of multiplicative noise models are considered. The finite-sample-size performance of our schemes is found to be relatively insensitive to variations in the additive noise distribution and the observation model in a specific example.