4.7 Article

Underwater acoustic signal denoising model based on secondary variational mode decomposition

期刊

DEFENCE TECHNOLOGY
卷 28, 期 -, 页码 87-110

出版社

KEAI PUBLISHING LTD
DOI: 10.1016/j.dt.2022.10.011

关键词

Underwater acoustic signal; Denoising; Variational mode decomposition; Secondary decomposition; Fluctuation-based dispersion entropy; Cosine similarity

向作者/读者索取更多资源

In this study, a new denoising method for underwater acoustic signals is proposed. The method utilizes optimized variational mode decomposition, fluctuation-based dispersion entropy threshold improvement, cosine similarity stationary threshold, and other techniques to effectively remove noise from the signals. Experimental results show that the proposed method achieves a significant improvement in denoising effect and has practical value.
Due to the complexity of marine environment, underwater acoustic signal will be affected by complex background noise during transmission. Underwater acoustic signal denoising is always a difficult problem in underwater acoustic signal processing. To obtain a better denoising effect, a new denoising method of underwater acoustic signal based on optimized variational mode decomposition by black widow optimization algorithm (BVMD), fluctuation-based dispersion entropy threshold improved by Otsu method (OFDE), cosine similarity stationary threshold (CSST), BVMD, fluctuation-based dispersion entropy (FDE), named BVMD-OFDE-CSST-BVMD-FDE, is proposed. In the first place, decompose the original signal into a series of intrinsic mode functions (IMFs) by BVMD. Afterwards, distinguish pure IMFs, mixed IMFs and noise IMFs by OFDE and CSST, and reconstruct pure IMFs and mixed IMFs to obtain primary denoised signal. In the end, decompose primary denoising signal into IMFs by BVMD again, use the FDE value to distinguish noise IMFs and pure IMFs, and reconstruct pure IMFs to obtain the final denoised signal. The proposed mothod has three advantages: (i) BVMD can adaptively select the decomposition layer and penalty factor of VMD. (ii) FDE and CS are used as double criteria to distinguish noise IMFs from useful IMFs, and Otsu algorithm and CSST algorithm can effectively avoid the error caused by manually selecting thresholds. (iii) Secondary decomposition can make up for the deficiency of primary decomposition and further remove a small amount of noise. The chaotic signal and real ship signal are denoised. The experiment result shows that the proposed method can effectively denoise. It improves the denoising effect after primary decomposition, and has good practical value.(c) 2022 China Ordnance Society. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据