This thesis develops and applies Bayesian model selection and inversion approaches to acoustic
seabed scattering and reflectivity 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 reflection). 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 reflection 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 reflection 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/reflection inversion
is able to distinguish between interface and volume scattering as the dominant mechanism.
%These invert either scattering
%data only or scattering and reflection data jointly, assume one of interface scattering, volume scattering,
%or volume and interface scattering, and use either fixed- or trans-D auto-regressive sampling. In addition,
%the procedure for determining the dominant scattering mechanism is validated on six simulated data set
%inversions where it accurately identifies the dominant scattering mechanism in five of the six test cases
%(the sixth case is ambiguous).
The inversion procedure is applied to data measured at several survey sites on the Malta Plateau
(Mediterranean Sea) to estimate {\it 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 data-information content to resolve scattering/
geoacoustic structure.
At the first site scattering was assumed ({\it 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 high-speed (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 $\sim$1 m of mud at the seafloor.
As a final component of this thesis, a polynomial spline-based parameterization for trans-D
geoacoustic inversion is developed for application to sites where sediment gradients (rather than
discontinuous layers) dominate. The parameterization is evaluated using data for a third site on
the Malta Plateau known to consist of soft mud with smoothly changing geoacoustic properties.
The spline parameterization is compared to the standard stack-of-homogeneous-layers parameterization
for the inversion of bottom-loss data. Inversion results for both parameterizations are in good
agreement with measurements on a sediment core extracted at the site. However, the spline
parameterization more accurately resolves the power-law like structure of the core density profile,
and represents the preferred model according to the deviance information criterion. / Graduate / 0373 / gavin.amw.steininger@gmail.com
| Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/5127 |
| Date | 02 January 2014 |
| Creators | Steininger, Gavin |
| Contributors | Dosso, Stanley Edward |
| Source Sets | University of Victoria |
| Language | English, English |
| Detected Language | English |
| Type | Thesis |
| Rights | Available to the World Wide Web |
Page generated in 0.0028 seconds