Multiscale Acoustic Holography of Soft Materials by Optimal Tarzan Scanning

Acoustic holograms capture both the amplitude and phase profiles of the sound scattered by small objects and therefore encode more information than conventional optical holograms that record only the intensity. Extracting that information can proceed either by reconstructing the three-dimensional sound field that generated the recorded hologram or by treating the hologram as an input to a high-dimensional inverse problem whose solution yields characterization and tracking data for the distribution of scatterers. Either analysis involves numerical reduction of massive data sets. We introduce an acoustic camera that acquires holograms by efficiently scanning a microphone across an arbitrarily large field of view in a pattern designed to provide full-field coverage with spatial resolution that improves with time. The scan pattern is generated with an iterative map that can be optimized for continuously improving sampling uniformity. We demonstrate the efficacy of this novel measurement technique through multiscale acoustic characterization of complex materials. This analysis reveals dynamical properties of the insonated systems, as well as their three-dimensional structure.