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A Source Localization Method Using Complex Variational Mode Decomposition.

Qiuyan Miao1, Xinglin Sun1, Bin Wu1

  • 1College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China.

Sensors (Basel, Switzerland)
|June 10, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel complex variational mode decomposition (CVMD) method for high-resolution passive sensor array source localization. The CVMD approach efficiently identifies multiple source locations with minimal data, overcoming limitations of traditional compressive sensing methods.

Keywords:
complex variational mode decompositioncompressive sensingfar-field sourcenear-field sourcesource localization

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Area of Science:

  • Array Signal Processing
  • Computational Electromagnetics
  • Statistical Signal Processing

Background:

  • Source localization using passive sensor arrays is crucial in various fields.
  • Compressive sensing (CS)-based methods offer high resolution but require dense grids, leading to computational inefficiency.
  • Existing CS methods struggle with coherent sources and limited snapshots.

Purpose of the Study:

  • To develop a more efficient and accurate source localization technique for passive sensor arrays.
  • To address the computational burden and limitations of traditional CS-based methods.
  • To enable high-resolution localization of near-field, far-field, and mixed sources, even with coherent signals and single snapshots.

Main Methods:

  • Extension of complex variational mode decomposition (CVMD) from nonstationary signal analysis to array signal processing.
  • Modeling the source localization problem as a time-domain frequency-modulated signal.
  • Decomposition of array measurements using CVMD to isolate signals from different source locations.
  • Model fitting to decomposed subsignals for estimating source direction and range.

Main Results:

  • The proposed CVMD-based method successfully localizes pure far-field, pure near-field, and mixed near-field/far-field sources.
  • Achieves high-resolution localization for coherent sources using only a single snapshot.
  • Demonstrates significantly reduced computing time compared to conventional CS methods.
  • Maintains accuracy and robustness under challenging conditions.

Conclusions:

  • CVMD offers a computationally efficient and high-resolution alternative for passive sensor array source localization.
  • The method effectively handles complex scenarios including coherent sources and limited data.
  • This approach advances the capabilities of array signal processing for accurate source identification.