A Novel Denoising Method for Ship-Radiated Noise

Abstract

Ship-radiated noise (SN) is one of the most critical signals in the complex marine environment; however, it is inevitably contaminated by the marine environment’s noise as well as noise from other equipment. Thus, the feature extraction and identification of SN becomes very arduous. This paper proposes a denoising method for SN based on successive variational mode decomposition (SVMD), the dual-threshold analysis based on fuzzy dispersion entropy (FuDE) and wavelet packet denoising (WPD), termed SVMD-FuDE-WPD. First, SVMD adaptively decomposes SN into certain intrinsic mode functions (IMFs), which can solve the parameter selection problem of variational mode decomposition (VMD) and suppress the mode mixing of empirical mode decomposition (EMD). After that, the FuDE-based dual-threshold analysis is used to accurately classify IMFs into signal IMFs, noise–signal IMFs and noise IMFs. Finally, the denoised signal could be obtained by reconstructing the signal IMFs and noise–signal IMFs that were denoised using WPD. The classical simulation experiments demonstrate the effectiveness of the proposed denoising method, which performs better than the other four existing denoising methods. And the measured SN experiments show that the attractor trajectories of the proposed method are smoother and more regular, which verifies the effectiveness of the proposed method.

A multiple waveguide invariant estimation method based on the warping transform and variational mode decomposition

“…This letter presents a multiple waveguide invariant estimation method based on the warping transform and variational mode decomposition (VMD) [6] from one-dimensional BISI. VMD uses a non-recursive algorithm framework to adaptively estimate all signal components and has been widely used in various fields [7,8]. In addition, the empirical mode decomposition [9], the multi-synchrosqueezing transform [10], and the deep learning method [11][12][13] are also widely used in mode separation or feature extraction.…”

“…To distinguish different β mn , an alternative solution is to separate the I mn (ω) using VMD from the warped BISI, then estimate the corresponding β mn using the cost function in Equation (7). Although the cost function in Equation ( 7) can only get an average value of β0 , it has been found through extensive simulations that the nonlinear dispersion of I mn (ω) can be partly reduced by substituting β0 into Equation (3).…”

Ship Shaft-Rate Electric Field Signal Denoising Method Based on VMD-MSS

“…In particular, the idea of combining multimodal decomposition with other denoising methods is very suitable for shaft-rate electric field signals with obvious line spectral features. Li [18] combined SVMD and (Discrete Wavelet Transformation) DWT to achieve effective suppression of Marine background noise in ship radiated noise signals, effectively improves the detection ability of passive sonar. Chen [19] proposed a marine turbulence denoising method based on (Empirical Mode Decomposition) EMD, which can effectively retain the detailed features of turbulence signals in a high noise background.…”

Multilayer Decomposition Denoising Empowered CNN for Radar Signal Modulation Recognition

“…Compared with EMD and LMD, VMD overcomes the problems of endpoint effects and modal aliasing and has other outstanding advantages in dealing with non-smooth signals and noise suppression. Recently, numerous enhanced VMD methods have been proposed, including sequential variational mode decomposition (SVMD) [13], [14] and multivariate variational modal decomposition (MVMD) [15]. By combining VMD and slope entropy (SloE), a new feature extraction method is presented to obtain high recognition accuracy of ship-radiated noise signals [16].…”