Analysis of Denoising Methods of Underwater Acoustic Pulse Signal Based on Wavelet and Wavelet Packet

Underwater acoustic countermeasures include active sonar countermeasures and passive sonar countermeasures. In order to achieve the best operational efficiency of jamming equipment, the generation of jamming signals must adapt to the development trend of underwater acoustic detection technology-nonlinear time-varying and broadband characteristics. Feature extraction is to map the high-dimensional original data to the low-dimensional transformation space through a certain mapping relationship, which can suppress a large amount of redundant information in the data and highlight the category information of the data. One of the applications of wavelet analysis in signal analysis and processing is to remove noise components from signals. In practical engineering applications, sampled signals are inevitably polluted by various noises and interferences. Through the analysis of noise characteristics, it can be seen that the wavelet denoising method is very effective in removing signal noise. In this paper, aiming at the signals with different spectrum distribution, we use various methods to de-noise in order to find the de-noising methods suitable for underwater acoustic pulse signals with different frequency characteristics, and thus find an effective means to detect signals.