Preprint: Global, and local optimization beamforming for broadband sources.

Area of Science:

• Acoustics
• Signal Processing
• Optimization

Background:

• Standard global optimization (GO) beamforming faces challenges with broadband acoustic sources due to frequency-dependent properties.
• The nonlinear energy function in standard GO beamforming can lead to local minima, complicating source identification.

Purpose of the Study:

• To develop an alternative energy function for global optimization (GO) beamforming specifically for acoustic broadband sources.
• To improve the accuracy and simplify the process of source identification and spectral reconstruction.

Main Methods:

• A cross-spectral matrix-fitting approach is used, parameterizing source properties over frequency.
• A novel broadband energy function is proposed, which averages the point spread function (PSF).
• Numerical analysis compares the proposed method with standard GO and CLEAN-SC (CLEAN based on source coherence).

Main Results:

• The proposed broadband energy function effectively averages the PSF, mitigating issues with local minima found in standard GO.
• The method demonstrates superior performance on synthetic monopoles compared to standard GO and CLEAN-SC.
• For real-world data, the proposed method and CLEAN-SC show similar, superior results over standard GO, with differing sensitivities to source assumption violations.

Conclusions:

• The proposed broadband energy function offers an improvement for GO beamforming of acoustic sources.
• It simplifies source identification and spectral reconstruction, outperforming existing methods in synthetic tests.
• The method shows robustness and potential for identifying complex acoustic sources, including multipoles with unknown characteristics.