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Related Experiment Videos

Second-order cone programming with probabilistic regularization for robust adaptive beamforming.

Xijing Guo1, Sebastian Miron2, Yixin Yang3

  • 1Key Laboratory of Ocean Acoustics and Sensing (Northwestern Polytechnical University), Ministry of Industry and Information Technology, Xi'an 710072, China xguo@nwpu.edu.cn.

The Journal of the Acoustical Society of America
|April 5, 2017
PubMed
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This summary is machine-generated.

Probabilistic regularization (PR) enhances superdirective array beamforming by improving directivity and robustness against sensor mismatches. This method offers superior performance compared to other robust adaptive beamforming techniques.

Area of Science:

  • Signal Processing
  • Array Signal Processing
  • Electromagnetics

Background:

  • Superdirective array beamforming aims to achieve high directivity from small arrays.
  • Sensor characteristic mismatches degrade beamformer performance and robustness.
  • Existing robust adaptive beamforming methods have limitations in achieving high directivity while maintaining robustness.

Purpose of the Study:

  • Introduce Probabilistic Regularization (PR) to enhance superdirective beamforming.
  • Achieve high directivity with guaranteed robustness against sensor mismatches.
  • Develop a PR method solvable via second-order cone programming.

Main Methods:

  • Probabilistic Regularization (PR) formulation for beamforming.
  • Second-order cone programming for solving the PR problem.

Related Experiment Videos

  • Statistical analysis and Monte Carlo simulations for parameter selection.
  • Experimental validation on a 3x3 uniform rectangular array without calibration.

    • Main Results:

    • PR method demonstrated robustness against sensor mismatches.
    • Achieved higher directivity compared to other robust adaptive beamforming approaches.
    • Effective regularization parameter selection based on system perturbation analysis.

    Conclusions:

    • Probabilistic Regularization is a viable approach for robust superdirective beamforming.
    • The proposed method offers improved directivity and robustness for uncalibrated arrays.
    • PR provides a statistically grounded framework for addressing sensor uncertainties in beamforming.