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Updated: Jan 20, 2026

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Spatially sparse sound source localization in an under-determined system by using a hybrid compressive sensing

Tongyang Shi1, Yangfan Liu1, J Stuart Bolton1

  • 1Ray W. Herrick Laboratories, School of Mechanical Engineering, Purdue University, West Lafayette, Indiana 47907-2099, USA.

The Journal of the Acoustical Society of America
|September 2, 2019
PubMed
Summary

This study introduces a hybrid method for sound source identification using fewer microphone measurements. It combines Equivalent Source Method with advanced algorithms to accurately pinpoint sound locations, reducing costs and complexity.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Computational Physics

Background:

  • Near-field Acoustical Holography (NAH) is effective for sound source identification and sound field reconstruction.
  • Traditional NAH requires numerous microphone measurements, which are costly and difficult in industrial settings.
  • Existing methods face challenges with measurement errors and spatial sampling rates.

Purpose of the Study:

  • To develop a method for reconstructing sound fields and identifying sound sources using a limited number of microphone measurements.
  • To address the economic and practical limitations of traditional acoustical holography techniques.
  • To enhance the accuracy of sound source localization in complex environments.

Main Methods:

  • An Equivalent Source Method (ESM) using monopole distributions was employed.
  • The study focused on an under-determined system created by combining ESM with a small number of measurements.
  • Wideband Acoustical Holography and l1-norm Convex Optimization were utilized to solve the inverse problem.

Main Results:

  • A novel hybrid method was proposed by integrating the strengths of Wideband Acoustical Holography and l1-norm Convex Optimization.
  • This hybrid approach effectively addresses the under-determined inverse problem inherent in using limited measurement data.
  • The method demonstrates potential for accurate sound source identification with reduced measurement requirements.

Conclusions:

  • The proposed hybrid method offers a cost-effective and practical solution for sound source identification.
  • It overcomes the limitations of traditional NAH by enabling accurate reconstruction with fewer measurements.
  • This technique is particularly beneficial for industrial applications where extensive measurements are challenging.