V.M. Artyushenko1, V.I. Volovach2, E.K. Samarov3

1 Moscow State University of Geodesy and Cartography (Moscow, Russia)

2 Volga Region State University of Service (Toglyatti, Russia)

2 MIREA – Russian Technological University (Moscow, Russia)

3 St. Petersburg State Maritime Technical University (St. Petersburg, Russia)

1 artuschenko@mail.ru; 2 volovach.vi@mail.ru; 3 omega511@mail.ru

To solve various problems, modern radio systems must ensure high noise immunity of the latter. When operating electronic equipment in electronic nodes and paths, vibroacoustic noise appears as a result of exposure to various adverse factors, such as mechanical vibrations, acoustic loads, etc. At the same time, additive and multiplicative noise occur. These factors significantly reduce noise immunity and complicate signal processing in electronic equipment. In addition, it is necessary to take into account the features of radio wave propagation that affect the characteristics of radio links and the conditions for receiving signals. For a more correct analysis and synthesis of radio engineering systems, the article proposes a solution based on the use of non-Gaussian models of the distribution of both useful signals and the noise affecting them.

The purpose of the study is to analyze and synthesize radio engineering systems using polygaussian models to describe random processes with arbitrary distribution.

It has been shown that polygaussian models effectively describe real random perturbations with non-Gaussian properties and allow obtaining multidimensional distributions of output processes. The selection of the number of output process vector coordinates to be considered is determined by the required granularity of the random process. An analytical expression for the multivariate density of the probability distribution of the output process was obtained, taking into account the process of both linear and nonlinear transformations. It is noted that with a parallel connection of an inertial nonlinear element and a linear inertial device for implementing output processes, they are summed up algebraically, while the final output process also retains a polygaussian character. Obtained an expression for the multivariate probability density of the sum of signal and non-Gaussian noise at the output of the linear detector. Said expression defines a multidimensional polyrisian distribution including both amplitude characteristics of the output process and statistical relationships between its components.

The results obtained confirm the effectiveness and practical significance of using polygaussian models for converting random signals and noises. At the same time, the proposed approaches make it possible to correctly describe and evaluate random processes with arbitrary distribution at the output of radio engineering systems in a complex and non-stationary noise environment.

Artyushenko V.M., Volovach V.I., Samarov K.E. Application of polygaussian models for random signal and noise conversion in radio engineering systems // Radiotekhnika. 2026. V. 90. № 8. P. 21−32. DOI: https://doi.org/10.18127/j00338486-202608-03

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