V.V. Makarenkov1, A.A. Shatalov2, V.A. Shatalova3, N.A. Kupriyanov4, S.V. Yakubovsky5

1 Military Space Academy named after A.F. Mozhaisky (St. Petersburg, Russia)
2 Mikhailovsky Military Artillery Academy (St. Petersburg, Russia)
3 St. Petersburg State University of Telecommunications n.a. prof. M.A. Bonch-Bruevich (St. Petersburg, Russia)
4 Krasnodar Higher Military Aviation School of Pilots n.a. Hero of the Soviet Union A.K. Serova (Krasnodar, Russia)
5 Research and Testing Center of the Central Research Institute of Aerospace Forces of the Ministry of Defense of the Russian Federation (Moscow, Russia)
1,5 makar8722@mail.ru, 2,3 gonta-gv@yandex.ru, 4 sektor-ussr@rambler.ru

The complex operating conditions of modern information systems for monitoring aerospace lead to unstable conditions for observing objects. In particular, the maneuvering of objects and the difficult conditions of the electromagnetic environment can lead to the fact that the condition of stationarity of the accepted implementation of the input random process (RP), laid down in the basis of the developed information processing algorithms, is not fulfilled. An unsteady RP is understood to be a RP that is homogeneous in time, the statistical characteristics of which change over time. As a result, the use of parameter estimation methods specifically designed to study the characteristics of a stationary joint venture to analyze the characteristics (samples) of a non-stationary joint venture entails the formation of biased and ineffective estimates. The use of estimates obtained in this way worsens such qualitative characteristics of the considered information systems as accuracy and speed. In this paper, we consider one of the varieties of deviation from the stationarity of the RP, which is the sum of a stationary series and a deterministic function against a background of noise. At the same time, if the mathematical expectation function (MEF) and (or) the variance of the deterministic function change slowly, then it is said that there is a trend in the accepted implementation of the input joint venture. The article suggests that during the operation of the considered information systems, monitoring (recognition) of the stationarity of information should be carried out, followed by correction of changes in time with the received RP (MEF and (or) variance), i.e. to make the developed algorithms adaptive to the non-stationary conditions of observing objects.

Goal – development of an adaptive algorithm for the recognition of stationary and non-stationary RP in conditions of parametric a priori uncertainty of signals statistical characteristics and interference.

A two-stage adaptive algorithm for digital processing of information received against the background of non-stationary interference in conditions of parametric a priori uncertainty of the statistical characteristics of signals and interference is presented. At the first stage of the algorithm, the characteristics of non-stationary interference are evaluated and the trend is eliminated. As a result of the evaluation, the problem of processing against the background of non-stationary interference is reduced to a similar problem of processing against the background of stationary interference, the solution of which is known and is carried out at the second stage of the algorithm.

Implementation options for an adaptive algorithm for recognizing stationary and non-stationary joint ventures are presented. It is shown that it is advisable to use modular arithmetic, in particular, a system of residual classes, to perform digital information processing in real time. The use of this computational procedure in the developed algorithm makes it possible to significantly improve the accuracy and speed of information systems, as well as simplify the architecture of the devices in question.

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