Maximum entropy inference of seabed properties using waveguide invariant features from surface ships.

Abstract

Acoustic data were recorded on two vertical line arrays (VLAs) deployed in the New England Mud Patch during the Seabed Characterization Experiment 2017 in about 75 m of water. The sound recorded during the passage of merchant ships permits identification of singular points for the waveguide invariant β for mode pairs (1,n):β1,n,for n=2,3,4,5, in the 15-80 Hz band. Using prior geophysical information and an acoustic data sample from the merchant ship KALAMATA, a geoacoustic model M of the seabed was developed. Then, using data samples from other merchant ships, a feature-ensemble maximum entropy method is employed to infer the statistical properties of geoacoustic parameter values for the sound speeds in a surface mud layer and a deep sand layer. Technical challenges include a sparsity of observed singular points, the unique identification of mode pairs for an observed singular point, and the deviation of the waveguide from horizontal stratification. A geoacoustic model M is developed that reproduced the observed β≈-1 for f < 20 Hz and mode cutoff features at about 15 Hz. The statistical low-frequency inference of the singular point structure from multiple ships provides evidence of an angle of intromission at the water sediment interface with an average sound speed ratio of about 0.986 and an average sound speed for the deeper sand layer of about 1775 m/s.