Ocean Acoustic Inversion

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Oceans are opaque to electromagnetic waves but transparent to sound; hence, acoustics is used for many underwater applications such as the remote sensing of seabed*properties/processes or the locations of sound sources (e.g., submarines, marine mammals), with geological, geotechnical, environmental and sonar/defence applications. However, acoustic remote sensing*requires nonlinear inversion, with quantitative model selection and uncertainty estimation required for meaningful interpretations. The proposed research builds on our long-term program in Bayesian (probabilistic) inversion for ocean acoustic remote sensing with six projects.***(1) Inversion for seabed acoustic scattering parameters and processes. Our initial work shows that inversion of backscatter data can resolve seafloor roughness and sediment heterogeneity spectra. We propose to develop quantitative model-selection*approaches to determine the relative importance of various physical scattering mechanisms and to estimate relevant*scattering parameters for different seabed types, to better understand the physics of seabed*scattering. ***(2) Estimation of laterally-variant seabed scattering parameters for naval databases or geotechnical*applications such as cable laying. This  is based on sequential Bayesian inversion of novel acoustic data sets collected using a mobile system comprising an acoustic source and receiver array towed near the*seabed by an autonomous underwater vehicle. ***(3) Extending our existing high-resolution reflectivity inversions for seabed geoacoustic parameters by including effects of shear waves, scattering, and dipping layers, with application to resolving dispersion (sound speed and attenuation frequency dependence) in marine sediments. ***(4) Tomographic (2D) inversion for seabed geoacoustic properties using full-field acoustic data recorded at a fixed*receiver array. A major component of quantitative nonlinear inversion in 2D involves developing new self-adaptive*sparse/irregular grids to parameterize the environment in a manner consistent with the resolving power of*the data to allow rigorous uncertainty estimation. ***(5) Acoustic source localization and uncertainty estimation, including the effects of uncertainty in ocean*environmental properties. Our initial work was in naval (passive sonar) applications, but we are moving into marine mammal*studies in collaboration with JASCO Research Ltd, a leading Canadian marine-technology company. Proposed*methods include a novel approach to matched-field localization with non-synchronized array systems/sub-systems,*and source ranging via modal dispersion (time-frequency analysis) at a single receiver. ***(6) Tracking an unknown number of vocalizing marine mammals using long-term acoustic monitoring data to provide a probabilistic solution from which information on*population and behaviour can be extracted. **