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March 25, 2026IET conference proceedings.0 citations

A new method for feature extraction of ship-radiated noise based on successive variational mode decomposition and dispersion entropy

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RZRui ZhangYLYuan LiXCXiaojun Chang

Key Points

  • The aim is to enhance feature extraction methods for ship-radiated noise to improve identification and detection.
  • Proposed a feature extraction method combining successive variational mode decomposition (SVMD) and dispersion entropy (DE).
  • Utilized SVMD for adaptive modal decomposition of ship-radiated noise signals.
  • Employed DE to analyze and characterize dynamic features of extracted modal components.
  • Validated the approach using a real-world ship dataset.
  • Demonstrated improved recognition effects compared to traditional methods.
  • Achieved better separability of features extracted from ship-radiated noise.
  • Confirmed effectiveness through real-world data validation.

Abstract

The feature extraction of ship-radiated noise can support ship target identification and is widely applied in ship detection and identification. However, the feature extraction method of ship-radiated noise have poor recognition effect and poor separability. To address these limitations, a feature extraction method based on successive variational mode decomposition (SVMD) and dispersion entropy (DE) is proposed in this paper. This method creatively combines SVMD with DE. First, SVMD is employed to perform adaptive modal decomposition on the signal. Subsequently, for the valid modal components obtained from the decomposition, DE is utilized to characterize the irregularities and dynamic variation features of each modal component. Finally, the validity of the proposed method is confirmed using real-world ship dataset.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69c37b54b34aaaeb1a67da94https://doi.org/10.1049/icp.2026.0143
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