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Spatial Wiener filter to reduce spatial aliasing with spherical microphone arrays.

Stefanie Brown1, Vidhyasaharan Sethu1, David Taubman1

  • 1School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, New South Wales, 2052, Australia.

The Journal of the Acoustical Society of America
|May 4, 2019
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Summary
This summary is machine-generated.

A new spatial Wiener filter (SWF) method improves the extraction of acoustic soundfield coefficients. This method reduces spatial aliasing errors and enhances reconstructed signals from spherical microphone arrays.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Three-dimensional acoustic sound fields are represented by spherical harmonic coefficients from microphone array data.
  • Extraction methods and truncation orders introduce spatial aliasing and truncation errors.
  • Current methods like regularized inverse and orthonormal extraction have limitations.

Purpose of the Study:

  • To propose a novel spatial Wiener filter (SWF) extraction method for acoustic sound fields.
  • To reduce spatial aliasing errors in spherical harmonic coefficients.
  • To improve the accuracy of reconstructed acoustic signals.

Main Methods:

  • Utilizing second-order statistics of sound field characteristics (signal power, source locations, noise).
  • Accounting for coefficients beyond the truncation order to mitigate spatial aliasing.
  • Implementing a filter that distinguishes between desired and undesired acoustic sources.

Main Results:

  • The SWF method effectively reduces spatial aliasing compared to existing techniques.
  • It demonstrates benefits for plane wave analysis under various source assumptions.
  • The SWF can extract coefficients beyond the array's traditional truncation limit.

Conclusions:

  • The proposed spatial Wiener filter offers superior performance in acoustic sound field coefficient extraction.
  • SWF provides a robust solution for minimizing errors in signal reconstruction.
  • This method advances the capabilities of spherical microphone array signal processing.