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An array pairing method for localizing distributed sources by acoustic beamforming.

Elias J G Arcondoulis1, Yu Liu1, Pengwei Xu1

  • 1Shenzhen Key Laboratory of Complex Aerospace Flows, Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen, Guangdong Province, 518055, People's Republic of China.

The Journal of the Acoustical Society of America
|February 3, 2020
PubMed
Summary
This summary is machine-generated.

The Array Pairing Method (APM) improves acoustic source localization by reducing signal misrepresentation. This novel beamforming technique enhances resolution for distributed sound sources.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Deconvolution algorithms can oversimplify distributed acoustic sources as point sources, leading to misrepresentation.
  • Accurate localization of distributed sound sources is crucial in various applications, including noise control and audio processing.

Purpose of the Study:

  • To introduce a novel acoustic beamforming concept, the Array Pairing Method (APM), designed to overcome limitations of traditional deconvolution algorithms.
  • To enhance the resolution and reduce misrepresentation of distributed acoustic sources.

Main Methods:

  • The Array Pairing Method (APM) involves an initial beamforming array followed by an iterative randomized array calculation.
  • Optimization criteria include minimizing the product of Maximum Sidelobe Level (MSL) and Main Lobe Width (MLW).
  • Validation through simulations of single and distributed sources, and experiments with single and dual speakers.

Main Results:

  • The APM demonstrated significant improvements in Maximum Sidelobe Level (MSL) and Main Lobe Width (MLW) compared to conventional methods.
  • Enhanced resolution was observed in the distributed source regions.
  • Experimental results confirmed the effectiveness of the APM in real-world acoustic scenarios.

Conclusions:

  • The Array Pairing Method (APM) offers a superior approach to acoustic source localization, particularly for distributed sources.
  • This method effectively alleviates the oversimplification issues inherent in deconvolution algorithms.
  • The APM shows promise for advancing acoustic imaging and source identification technologies.