Determination of Seabed Acoustic Scattering Properties by Trans-Dimensional Bayesian Inversion

This thesis develops and applies Bayesian model selection and inversion approaches to acoustic seabed scattering and re ectivity data to estimate scattering and geoacoustic parameters with uncertainties, and to discriminate the relative importance of interface and volume scattering mechanisms. Determining seabed scattering mechanisms and parameters is important for reverberation modelling and sonar performance predictions. This thesis shows that remote acoustic sensing can provide efficient estimates of scattering properties and mechanisms with uncertainties, and is well suited for the development of bottom-scattering databases.;An important issue in quantitative nonlinear inversion is model selection, i.e., specifying the physical theory, appropriate parameterization, and error statistics which describe the system of interest (acoustic scattering and re ection). The approach developed here uses trans-dimensional (trans-D) Bayesian sampling for both the number of sediment layers and the order (zeroth or first) of auto-regressive parameters in the error model. The scattering and re ection data are inverted simultaneously and the Bayesian sampling is conducted using a population of interacting Markov chains. The data are modelled using homogeneous fluid sediment layers overlying an elastic basement. The scattering model assumes a randomly rough water-sediment interface and random sediment-layer volume heterogeneities with statistically independent von Karman spatial power spectra. A Dirichlet prior distribution that allows the sediment layers and basement to have different numbers of parameters in a trans-D inversion is derived and implemented. The deviance information criterion and trans-D sampling are used to determine the dominant scattering mechanism for a particular data set.;The inversion procedure is developed and validated through several simulated test cases, which demonstrate the following. (i) Including re ection data in joint inversion with scattering data improves the resolution and accuracy of scattering and geoacoustic parameters. (ii) The trans-D auto-regressive model improves scattering parameter resolution and correctly differentiates between strongly and weakly correlated residual errors. (iii) Joint scattering/re ection inversion is able to distinguish between interface and volume scattering as the dominant mechanism.;The inversion procedure is applied to data measured at several survey sites on the Malta Plateau (Mediterranean Sea) to estimate in-situ seabed scattering and geoacoustic parameters with uncertainties. Results are considered in terms of marginal posterior probability distributions and profiles, which quantify the effective datainformation content to resolve scattering geoacoustic structure.;At the first site scattering was assumed (a priori) to be dominated by interface roughness. The inversion results indicate well-defined roughness parameters in good agreement with existing measurements, and a multi-layer sediment profile over a highspeed (elastic) basement, consistent with independent knowledge of sand layers over limestone.;At the second site no assumptions were made about the scattering mechanism. The deviance information criterion indicated volume scattering to be the dominant scattering mechanism. The scattering parameters and geoacoustic profile are well resolved. The parameters and preference for volume scattering are consistent with a core extracted at the site which indicated a sediment layer which included large (0.1 m) stones underlying ∼1 m of mud at the seafloor.