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Fast deconvolved beamforming for arbitrary arrays based on off-grid sparse Bayesian learning.

Jianli Huang1, Yu Wang1, Zaixiao Gong1

  • 1State Key Laboratory of Acoustics, Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, Chinahuangjianli@mail.ioa.ac.cn, wy@mail.ioa.ac.cn, gzx@mail.ioa.ac.cn, nhq@mail.ioa.ac.cn, wangj@mail.ioa.ac.cn, whb@mail.ioa.ac.cn.

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This study introduces off-grid sparse Bayesian learning for deconvolved beamforming, enhancing spatial resolution for real-world targets. The improved method overcomes limitations of traditional techniques for shift-variant beam patterns and targets off sampling grids.

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Area of Science:

  • Signal Processing
  • Array Signal Processing
  • Computational Electromagnetics

Background:

  • Deconvolved beamforming (dCv) enhances spatial resolution without increasing array size.
  • Traditional dCv struggles with shift-variant beam patterns and targets not on sampling grids.
  • Accurate spatial localization is crucial in various sensing applications.

Purpose of the Study:

  • To extend off-grid sparse Bayesian learning (OGSBL) to deconvolved beamforming (dCv).
  • To address limitations of dCv concerning shift-variant beam patterns and off-grid targets.
  • To improve spatial resolution and accuracy in beamforming techniques.

Main Methods:

  • Generalized convolutional model incorporating beam pattern per angle.
  • Parameterization of sampled locations on coarse grids to reduce modeling errors.
  • Control of output beam count to cover spatial regions of interest for faster convergence.

Main Results:

  • The proposed OGSBL-enhanced dCv effectively handles shift-variant beam patterns.
  • Accurate localization of targets not on sampling grids is achieved.
  • Simulation results demonstrate the method's good performance and accuracy.

Conclusions:

  • The integration of OGSBL with dCv offers a robust solution for enhanced spatial resolution.
  • This approach overcomes key limitations of conventional dCv.
  • The method shows significant potential for advanced beamforming applications.