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The Intensity Vector Autonomous Recorder (IVAR) measures acoustic particle velocity and pressure simultaneously. IVAR was deployed on the seabed during the 2017 Seabed Characterization Experiment (SBCEX) with the primary objective to study sound propagation within underwater waveguides for which the seabed consists of fine-grained, muddy sediments. In this study, a Bayesian framework is applied to underwater noise recorded by IVAR from a cargo ship traversing the central region of the SBCEX2017 area for the purpose of inversion to characterize sediment properties. The vector acoustic data are in the form of a bounded, nondimensional form known as circularity, a quantity that is independent of the ship noise-source spectrum and that can be interpreted as the normalized curl of active intensity. The inversion model space for the seabed consists of a low-compressional speed layer and underlying basement half-space, with each having compressional and shear components. The interpretative model for producing a replica of the data is based on the plane wave reflection coefficient for a layered, elastic seabed in conjunction with the depth-dependent Green&#x2019;s function that is integrated in the complex wave number plane to obtain pressure and particle velocity fields. The small change in water depth between the location of the ship source and IVAR is addressed using adiabatic mode theory. The inversion results exhibit slow variation over the 20-min observation period, representing approximately 5 km of travel by the ship source.

Range-Dependent Inversion for Seabed Parameters Using Vector Acoustic Measurements of Underwater Ship Noise