Detection of Markovian Signals on the Background of Markovian Interferences. Prior Uncertainty Case

In many cases one can faced with situation of unknown and unstable statistical models of signals and interferences. It is known that markovian processes give good chance for simulation of random processes with non-Gaussian distribution. In this paper the basic approaches to synthesis of signal detection algorithms are considered under the conditions of parametrical aprioristic uncertainty of both signal and interference situations.