RESEARCH OF THE INFLUENCE OF STOCHASTIC INTERFERENCE OF VARIOUS NATURES ON THE PARAMETRIC STABILITY OF RADIO SIGNALS

The article investigates the influence of stochastic interference of various natures on the parametric stability of radio signals. It is established that each type of noise has a different effect on the metrological characteristics of the signal - amplitude, frequency, phase and waveform. In particular, the most significant effect on the signal parameters is exerted by brown noise and Gaussian noise, which are characterized by a complex structure of spectral density and high intensity in certain frequency ranges. While uniform, blue and violet noise have a minimal effect on the main metrological parameters, which opens up opportunities for their use as background or compensating components in data transmission systems. The practical value of the results obtained lies in the possibility of adapting digital signal processing algorithms to the conditions of the presence of various types of noise, which is especially important for telecommunication systems operating in difficult radio-electronic conditions. The application of approaches to the assessment and compensation of the impact of noise allows to increase the accuracy of measurements, reduce errors in the transmission of information, and also to improve the means of protecting signals from interference of natural and artificial origin.In the future, further research may be aimed at the development of adaptive filters and noise suppression algorithms taking into account the type of interference, as well as the use of machine learning methods for classifying signals by type of interference. In addition, it is advisable to study the combined effect of several types of noise simultaneously, as well as the influence of nonlinear properties of radio channels on the effectiveness of metrological control of signal parameters. In general, the results of the work contribute to the development of scientific approaches to modeling and analyzing signals in stochastic conditions, which is important for improving technologies in such areas as digital television, mobile communications, satellite communications, navigation systems and radar.