Robust generation of invariant detectors in uncertain noise environments

New adaptive asymptotically robust invariant algorithms are proposed, and examined. These algorithms are used for the detection of signals with some unknown parameters observed in additive noise with unknown distribution. The algorithms are based on asymptotically robust invariant (ARI) algorithms previously developed by the authors. The extended model of approximately finite probability distributions (q-point model) is employed for algorithm synthesis. Adaptation is achieved by estimating and optimizing the algorithm for the unknown parameters of the q-point model. The algorithms characteristics were obtained by computer simulation for the case of BPSK modulation.