A Physics-Based Inversion of Multibeam Sonar Data for Seafloor Characterization

Abstract

A physics-based algorithm has been developed for the inversion of multibeam sonar survey data for sediment properties. The algorithm relies on high-frequency acoustical models of seafloor scattering to estimate sediment properties, taking as input the calibrated backscatter intensity time series data for multiple incidence angles. The inversion proceeds in three stages to produce estimates for a suite of geoacoustic and physical parameters of the seafloor, which include sediment attenuation and strengths of interface and volume scattering in the first stage, surface roughness and reflectivity in the second stage, and porosity, density, and sound-speed ratios and mean grain size in the third and final stage. The algorithm uses a Monte-Carlo approach to determine the uncertainties in inversion-derived sediment properties based on the measured statistics of seafloor backscatter. This assessment also takes into account the uncertainties associated with the empirical relations utilized in the final stage of inversion to determine sediment properties from reflectivity. The performance and accuracy of the algorithm have been evaluated through implementation in the processing of field data recorded from Sequim Bay, WA, USA, in 2019. Comparison of inversion output with ground-truth measurements demonstrates the effectiveness and robustness of the algorithm in seafloor characterization with multibeam sonars.