Closed-aperture unbounded acoustics experimentation using multidimensional deconvolution

Area of Science:

• Acoustics
• Wave Propagation
• Signal Processing

Background:

• Physical acoustic experiments are often hindered by boundary reflections.
• Accurate characterization of scattering objects requires isolating their unique wave imprints.

Purpose of the Study:

• To introduce and validate multidimensional deconvolution (MDD) for removing boundary scattering in acoustic experiments.
• To obtain Green's functions solely associated with a scattering object of interest.

Main Methods:

• Developed a novel decomposition method for in/out wavefield separation on arbitrary curved surfaces.
• Applied multidimensional deconvolution (MDD) to post-process experimental data.
• Validated results using synthetic simulations in a 2D acoustic waveguide.

Main Results:

• MDD effectively removed domain boundary scattering imprints from experimental data.
• Obtained Green's functions between all points on the recording surface, fully sampling the scattered field.
• Experimental results matched synthetic simulations, confirming MDD's efficacy.

Conclusions:

• MDD is a powerful and general method for obtaining experimental Green's functions.
• The technique enables accurate characterization of wavefield scattering from inhomogeneous scatterers.
• This approach significantly improves the quality and interpretability of acoustic wave propagation data.