INVESTIGATION OF SPREAD SPECTRUM SIGNAL ANALYSIS METHODS IN MODERN COMMUNICATION SYSTEMS

The article examines modern approaches to the analysis of spread spectrum signals, particularly those based on pseudorandom frequency hopping and chirp spectrum expansion. The main focus is on the development and optimization of efficient time-frequency analysis methods for the identification and monitoring of such signals under real-world conditions, considering their complexity and dynamic nature. Special attention is given to the application of methods that ensure high accuracy, efficiency, and resistance to interference, which is extremely important in environments with high radio frequency activity. A combined approach is proposed, incorporating the Fast Fourier Transform, spectrograms, and continuous wavelet transform using Morlet wavelets, the "Mexican hat" wavelet, and a specially adapted chirp wavelet. This approach allows for obtaining detailed information about the frequency and time characteristics of signals and ensures accuracy in detecting non-stationary components. The article presents the results of studies on signals with pseudorandom frequency hopping and chirp spectrum expansion. Particular attention is paid to the impact of frequency dynamics and noise conditions on the effectiveness of signal identification. A comparison of different analysis methods demonstrates the high efficiency of continuous wavelet transform combined with traditional spectral methods for recognizing non-stationary signals and determining their key frequency components. The obtained results can be useful for the development of radio monitoring systems, the analysis, and classification of complex signals in various fields, such as telecommunications, radar, and radio monitoring. The research has practical significance for the creation of algorithms for signal detection and analysis in modern wireless communications and specialized communication systems. The developed approaches can be applied in a wide range of applications, including civilian and military systems that require high analysis accuracy and resistance to interference, as well as in automated monitoring and recognition of complex signals.