Prospects for the Application of Wavelet Analysis in the Problems of Classification of Hydroacoustic Signals

Wavelet transformation is widely used for signal analysis, which, unlike the classical Fourier transform, make it possible to simultaneously detect low-frequency and high-frequency characteristics of signals on different time scales (i.e., it is feasible to examine how the frequency spectrum of signals varies over time). The theory of wavelet transformation relies on the concept of multi-scale analysis, which involves examining the signal at various frequencies and resolutions. At the same time, it increases the flexibility of signal processing methods and expands the scope of their application. Wavelet transformation is also widely used in information and telecommunication systems, physics and astrophysics, mathematics, seismology, image compression, speech recognition, medicine etc. Moreover, based on wavelet analysis of non-stationary and nonlinear echoes of underwater objects, it is possible not only to classify and identify objects, but also to solve these problems in highly noisy and complex conditions for detecting hydroacoustic signals. Further research using wavelet analysis opens up new perspectives for the development and improvement of systems used to monitor and analyze complex signals in various environments. Wavelet transformation open up new horizons for scientific research, become an integral part of modern signal analysis technologies, contribute to a more effective solution of complex problems in different fields of technology and science, which ensures high accuracy and reliability of the results obtained. In addition, due to the ability to localize in the time-frequency domain and resistance to interference, wavelet transforms are used in highly efficient modern systems for detecting and identifying underwater objects. Further development of scientific research in this area will certainly further expand the possibilities of wavelet analysis, making it an even more powerful tool in the field of signal and information processing.