Detection of the Markov Signals in a Mixture with the Markov Correlated Clutters using Autoregressive Models

New adaptive algorithms of detection of correlated signals on background of correlated clutter are proposed. Algorithms are based on autoregressive Markovian model of random process. Statistical hypothesis about parameters of autoregressive model of narrow band random process are checked. Viability and efficiency of new algorithms proves to be true by using statistical modeling as well as by processing real signals of weather radar