V.N. Zhurakovsky - Ph.D. (Eng.), Associate Professor, SM-6 Department, Bauman Moscow State Technical University. E-mail: zhurakovsky@sm.bmstu.ru V.R. Kuznetsov - Engineer, SM2-2 Department, Bauman Moscow State Technical University. E-mail: wator1@mail.ru S.I. Silin - Ph.D. (Eng.), Associate Professor, SM-5 Department, Bauman Moscow State Technical University. E-mail: sm2-2@inbox.ru

Modern signal processing is the extraction of certain information (parameters) of the signal for further use. In particular, the signal parameters can recognize its appearance, with a priori known types of signals. Existing approaches of designing signal recognition algorithms do not allow to fully ensure the correct processing of these parameters, as it does not take into account some important factors. These factors are associated primarily with the noise that does not allow you to uniquely identify useful signals in a noisy environment. This problem was solved by the methods of parametric probability of selection, which are widely used in statistics, acoustics and radar. The method used is to combine the signals having similar characteristics parametric allocated from the received signals. Another problem that arises in the process step is to determine the ambiguity parameter selected by selection signals, extraction necessitates more probable signal form. Extraction most veroyatnogovida signal transmitted by the parameters is achieved by a formula derived by using the apparatus of probability theory and mathematical statistics for the a posteriori probability. Thus, the developed approach to synthesizing signal recognition algorithm allows for «soft» signal recognition algorithm. The developed algorithm has been investigated in deciding whether a signal is present when applying a complex mixture of the specified signal and a set of interfering signals.

 

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