A New Method for Denoising Underwater Acoustic Signals Based on EEMD, Correlation Coefficient, Permutation Entropy, and Wavelet Threshold Denoising

Abstract

The complexities of the marine environment and the unique characteristics of underwater channels pose challenges in obtaining reliable signals underwater, necessitating the filtration of underwater acoustic noise. Herein, an underwater acoustic signal denoising method based on ensemble empirical mode decomposition (EEMD), correlation coefficient (CC), permutation entropy (PE), and wavelet threshold denoising (WTD) is proposed. Furthermore, simulation experiments are conducted using simulated and real underwater acoustic data. The experimental results reveal that the proposed denoising method outperforms other previous methods in terms of signal-to-noise ratio, root mean square error, and CC. The proposed method eliminates noise and retains valuable information in the signal.

Keywords

Ensemble empirical mode decomposition / Correlation coefficient / Permutation entropy / Wavelet threshold denoising / Underwater acoustic signal denoising

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