From geoacoustic inversion to seabed tomography using a distributed network of sources and receivers

Understanding and predicting acoustic propagation at sea is critical for many marine applications, from noise pollution forecasts to underwater warfare. To do so in coastal waters requires knowledge of the seabed geoacoustic properties; estimating those from ocean acoustic data is called geoacoustic inversion. Historically, geoacoustic inversion considers acoustic propagation between a fixed (or linearly moving) source and a receiver (or array of receivers), usually leading to the estimation of a depth-dependent geoacoustic profile, assumed to be representative of the propagation track. In this talk, we will show how low-cost instrumentation and advanced signal processing methods (warping time-frequency analysis, trans-dimensional inversion, and machine learning) enable estimation of the spatial variability of seabed geoacoustic properties. Several examples will be presented, all based on data collected on the New England Mud Patches during the Seabed Characterization Experiments. We will notably illustrate how the proposed methods enable characterization of the spatial variability of the muddy seabed sediments at the scale of a single mud patch, as well as the inter-comparison of mud properties between several distant mud patches. [Work supported by the Office of Naval Research.]