Compressive acoustic holography with block-sparse regularization

Area of Science:

• Acoustics
• Signal Processing
• Numerical Analysis

Background:

• Sparse reconstruction methods like Compressive Sensing are vital for wideband acoustic array processing.
• These methods struggle with non-sparse sound fields (e.g., near-fields, reflective environments, extended sources), leading to poor reconstruction.
• Existing techniques may not adequately capture complex acoustic phenomena.

Purpose of the Study:

• To develop and evaluate a novel sparse analysis prior method for sound field reconstruction.
• To address limitations of traditional sparse methods in analyzing non-sparse acoustic scenarios.
• To introduce the Fused Total Generalized Variation (F-TGV) method for near-field acoustic analysis.

Main Methods:

• Development of the Fused Total Generalized Variation (F-TGV) method.
• Promoting block-sparse solutions by encouraging sparsity in both the solution and its spatial derivatives.
• Numerical simulations and experimental validation to assess performance.
• Comparison with established acoustic reconstruction methods.

Main Results:

• The F-TGV method demonstrates suitability for analyzing both compact and spatially extended acoustic sources.
• The method achieves robust sound field reconstruction even in the presence of noise.
• It provides effective wideband reconstruction for sound fields that are not inherently sparse.
• F-TGV outperforms established methods in specific non-sparse acoustic scenarios.

Conclusions:

• The F-TGV method offers a promising advancement in acoustic array processing.
• Its generality and robustness make it suitable for a wide range of challenging acoustic environments.
• The method enhances the capability to reconstruct complex, non-sparse sound fields accurately.