Research on Underwater Complex Target Signal Extraction Method Using Wiener and EMD Algorithms

Due to the complexity and variability of the underwater environment, the target signal is often covered by complex environmental noise. In this paper, a combined algorithm based on Wiener wavelet threshold method and empirical mode decomposition (EMD) method is proposed to realize signal feature extraction in complex chaotic underwater acoustic environment. Firstly, Wiener filtering is performed on the original signal to remove a large amount of random noise; then the preprocessed signal is decomposed by EMD, the correlation between all modal components and the original signal is compared, the noise component is subjected to wavelet transform and noise reduction, and finally all modal components are reconstructed. Simulation results show that compared with other methods, the combined algorithm proposed in this paper has higher output signal-to-noise ratio and the smallest root mean square error. This research has a very important guiding role for the application of hydroacoustic engineering.