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Updated: Dec 29, 2025

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Adaptive reweighting homotopy algorithm based compressive spherical beamforming with spherical microphone arrays.

Shijia Yin1, Zhigang Chu1, Yongxiang Zhang1

  • 1State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, People's Republic of China.

The Journal of the Acoustical Society of America
|February 3, 2020
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A new adaptive reweighting homotopy (ARH) algorithm for compressive spherical beamforming (CSB) accurately identifies acoustic sources. This ARH-CSB method improves performance in low signal-to-noise ratio environments without needing prior SNR estimation.

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Area of Science:

  • Acoustics
  • Signal Processing
  • Array Signal Processing

Background:

  • Compressive spherical beamforming (CSB) utilizes spherical microphone arrays for high spatial resolution and sidelobe suppression, particularly at medium to high frequencies.
  • Existing CSB methods often rely on accurate signal-to-noise ratio (SNR) estimation, limiting their applicability in challenging acoustic environments.

Purpose of the Study:

  • To adapt the adaptive reweighting homotopy (ARH) algorithm for compressive spherical beamforming (CSB), creating the ARH-CSB method.
  • To develop a CSB technique that does not require a priori SNR estimation.
  • To enhance the identification and quantification of acoustic sources, especially under low SNR conditions.

Main Methods:

  • The adaptive reweighting homotopy (ARH) algorithm was adapted to the CSB framework, resulting in the ARH-CSB method.
  • ARH-CSB iteratively determines the source support set and adaptively searches for weights while estimating source strength.
  • The performance was evaluated through simulations and experimental data.

Main Results:

  • ARH-CSB effectively identifies acoustic sources.
  • The proposed method demonstrates superior adaptability to low SNR conditions compared to traditional ℓ1-norm minimization and iterative reweighted ℓ1-norm minimization algorithms.
  • ARH-CSB exhibits enhanced robustness, higher accuracy in quantifying weak sources, and faster computation speed.

Conclusions:

  • The ARH-CSB algorithm offers a robust and efficient solution for acoustic source identification using spherical microphone arrays.
  • This method overcomes the limitation of requiring prior SNR estimation, making it more versatile for real-world applications.
  • ARH-CSB provides significant advantages in accuracy and speed, particularly in low SNR scenarios.