Journal of Low Frequency Noise, Vibration and Active Control (Mar 2023)

Improvement of orthogonal matching pursuit deconvolution beamforming method for acoustic source identification

  • Jinyuan Zhang,
  • Yiyun Wen,
  • Jiahui Yan,
  • Xiaoguang Yang,
  • Zhigang Chu

DOI
https://doi.org/10.1177/14613484221122097
Journal volume & issue
Vol. 42

Abstract

Read online

The deconvolution approach for the mapping of acoustic sources (DAMAS) based on orthogonal matching pursuit (OMP-DAMAS) has attracted much attention due to its advantages of high spatial resolution and excellent capability to suppress spurious sources. In this paper, we propose an improved version of OMP-DAMAS based on fast Fourier transformation (FFT), abbreviated as FFT-OMP-DAMAS. This method assumes that the array point spread functions (PSFs) are spatially shift-invariant. The sum of the product of the acoustic source distribution and PSFs is converted into a convolution form, which is further converted into a product in the wave number domain. With these conversions, FFT can be used to improve the solving speed. Both simulations and experiments show that the proposed method not only inherits the advantages of OMP-DAMAS in terms of spatial resolution and spurious source suppression but also significantly improves the computational efficiency compared with OMP-DAMAS.