I.V. Malygin1, S.A. Belkov2, D.A. Mikhailik3, K.V. Stafeev4

1-4 Ural Federal University named after the first President of Russia B.N. Yeltsin (Ekaterinburg, Russia)

1 pit_pit2@mail.ru; 2 srgb@mail.ru; 3 dmtr-mih@yandex.ru; 4 krlstafeev@gmail.com

The main purpose of the information transmission system is to transfer useful information between its users reliably and accurately. At the same time, it would be advisable to supplement the functionality of the information transmission system with the ability to analyze interference in the communication channel during the transmission of a message. In the case of analysis of damage to the useful signal, which may occur due to interference of various types in the propagation medium, the information transmission system can use the results of such analysis to improve noise immunity, to collect statistics, to control electromagnetic compatibility. It is known that optimal processing of noise-like signals is carried out using a correlator or a matched filter, but these classical devices might be complemented with a neural network, and then in addition to determining the correlation function, it is the neural network that is able to analyze a signal damaged by interference, as shown by the authors in their previous works. In this case, for the correct training of a neural network, samples of a useful signal damaged by various types of jamming are needed. This article discusses methods for the formation of training images for a neural network designed to determine the period of pulse interference acting on an M-sequence as a known signal. Two techniques are suggested. They are digital modelling and experimental (laboratory) method. The first one is based on the inverting some elements (chips) of the original M-sequence located in certain segments whose lengths are random. The inversion is performed by the program written in C++ language. The second approach involves a special installation that consists of a personal computer, an Arduino microcontroller, a useful signal transmitter, a receiver and a periodic interference generator. The objective of each method is to obtain a matrix of damaged chips in a chain of M-sequences. Such matrix was called an “error profile” by the authors. The characteristics of the error profile obtained for certain interference parameters (jamming pulse period and duration) according to suggested methods can be used as training data for the neural network designed for jamming classification.

Malygin I.V., Belkov S.A., Mikhailik D.A., Stafeev K.V. Development of methods for generating examples that train a neural network to detect and classify interference in the structure of a useful signal. Radiotekhnika. 2024. V. 88. № 6. P. 121−129. DOI: https://doi.org/10.18127/j00338486-202406-15 (In Russian)

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