Adaptive space-time filtration synthesis under unknown total noise matrix

The problem of synthesis of adaptive space-time filtering filtering, which is optimal by criterion of information parameter selection at unknown matrix of total noises, is considered. It is shown that the proposed transformation of unknown parameters makes it possible to divide them into informative and non-informative, discarding of which greatly simplifies the optimal algorithm of adaptive space-time processing. The considered approach to solving the synthesis problem allows us to isolate the minimum number of informative adaptation parameters and obtain optimal and fairly simple adaptive space-time filtering structures that generalize the classical Schirman-Widrow autocorrelation algorithms.