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ICEEMDAN-RPE-AITD algorithm for magnetic field signals of magnetic targets

  • 0Naval University of Engineering, Wuhan, 430033, Hubei, China.
Scientific Reports +

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February 22, 2025

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February 22, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

This study introduces an ICEEMDAN-RPE-AITD algorithm for denoising magnetic target signals. The novel method effectively removes noise, enhancing signal clarity for improved target detection.

Area Of Science

  • Geophysics
  • Signal Processing
  • Data Analysis

Background

  • Magnetic target signals contain crucial target information but are often corrupted by background and sensor noise.
  • Effective denoising is essential for accurate interpretation of magnetic field data.

Purpose Of The Study

  • To develop and validate a novel algorithm for denoising magnetic target signals.
  • To improve the signal-to-noise ratio and accuracy of magnetic field measurements.

Main Methods

  • Proposed an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), reverse permutation entropy (RPE), and adaptive interval threshold denoising (AITD) algorithm.
  • Decomposed signals into intrinsic mode functions (IMFs), classified IMFs using RPE and dual thresholds, and applied AITD for denoising.
  • Validated the algorithm using ship model magnetic field signals and measured data, employing metrics like signal-to-noise ratio, root mean square error, noise intensity, and correlation dimension.

Main Results

  • The ICEEMDAN-RPE-AITD algorithm demonstrated significant effectiveness in denoising magnetic target signals.
  • Quantitative evaluation using signal-to-noise ratio and root mean square error confirmed the algorithm's performance.
  • Analysis of measured data further validated the algorithm's capability in real-world scenarios.

Conclusions

  • The proposed ICEEMDAN-RPE-AITD algorithm is a robust and effective solution for denoising magnetic target signals.
  • This method enhances the quality of magnetic field data, facilitating better target feature extraction and analysis.
  • The study provides a valuable tool for geophysical exploration and magnetic surveying applications.

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