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Design and implementation of a space domain spherical microphone array with application to source localization and

Mingsian R Bai1, Yueh Hua Yao1, Chang-Sheng Lai1

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Summary

This study compares delay-and-sum beamformers for spherical arrays. Compressive sensing (CS) offers superior sound source separation quality over Tikhonov regularization (TIKR), despite higher computational costs.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Spherical arrays are crucial for advanced acoustic applications.
  • Delay-and-sum (DAS) beamformers are widely used but require careful formulation.
  • Understanding the performance of different beamforming domains (modal vs. space) is essential.

Purpose of the Study:

  • To analyze and compare four delay-and-sum (DAS) beamformers in modal and space domains for open and solid spherical apertures.
  • To experimentally validate the performance of a 3D-printed spherical microphone array for sound source localization and separation.
  • To evaluate the effectiveness of Tikhonov regularization (TIKR) and compressive sensing (CS) for source signal amplitude extraction.

Main Methods:

  • Numerical simulations of beampatterns for open and solid spherical DAS arrays.
  • Experimental validation using a 3D-printed spherical array with 32 micro-electro-mechanical system microphones.
  • Source localization via minimum variance distortionless response (MVDR) beamformer, followed by TIKR and CS for signal separation.

Main Results:

  • Solid spherical DAS arrays exhibit slightly narrower mainlobes than open arrays.
  • Modal domain DAS arrays show higher sidelobes than space domain arrays due to discrete approximation.
  • Compressive sensing (CS) demonstrated superior sound source separation quality compared to Tikhonov regularization (TIKR).

Conclusions:

  • The proposed spherical array system is validated through simulations and experiments.
  • CS provides better separation performance than TIKR for acoustic source separation, albeit with increased computational complexity.
  • The study highlights the trade-offs between different beamforming techniques and regularization methods in spherical array applications.