The purpose of the thesis is to analyze the properties of acoustic sound field in the Sizihwan Bay Marine Test Field (SBMTF), and to conduct geoacoustic inversion using the measured data. Two experiments were carried out during February, 2009, and March, 2010. The source was UW350, and the receivers were ITC 6050 hydrophones. The transmitted frequencies lie between 350 Hz and 1250 Hz. On the analysis of acoustic propagation, the study calls for the application of OASES for the analysis of transmission loss and effects of range dependency. Moreover, the uncertainty analysis due to environmental factors was carried out based upon probabilistic approach. For the inversion analysis, the sensitivity of each environmental parameter was first analyzed, and those parameters with high sensitivity were chosen for inversion. Inversion was conducted by the application of SAGA. The results have shown that, due to the fact that the SBMTF is an very shallow water environment with water depth less than 30 m, the acoustic sound field is strongly affected by the boundaries. From the uncertainty analysis, it shows that the transmission loss has high degree of uncertainty resulting from seabed property due to its lack of accurate measurement. The inversion results for water depth and seabed sound speed were obtained, and compared with the measured data. This research calls for experimental design, data processing, software application, and result analysis, offering an overall understanding of the properties of SBMTF that is valuable for future study.

This work focuses on developing an inversion scheme to estimate water-column sound-speed fields in three dimensions. The inversion scheme is based on a linearized perturbative technique which utilizes estimates of modal travel times. The technique is appropriate in the littoral ocean where measurements are made across range and cross-range distances greater than 10 km to ensure sufficient modal dispersion. Previous applications of then inversion technique has been limited to one or two dimensions and/or focused primarily on the seabed. Compared to past applications, the accuracy and uncertainty of the solution is improved by employing approximate equality constraints within the context of \textit{a priori} estimates of model and data covariances. The effectiveness of the constrained technique is explored through a one-dimensional example. The robustness of the technique is illustrated by introducing different types of errors into the inversion and considering the accuracy. A further examination of the technique is given by exploring a three-dimensional example. Several case studies are presented to investigate the effects of different levels of environmental variability and spatial sampling. / text

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

Sound propagation can be greatly affected by seabed, especially in shallow water, therefore by understanding the geoacoustic parameters of sea bottom can help to improve the performance of sonar systems. In this study, ship noise collected by the vertical line array (VLA) in South China Sea experiment of the Asian Seas International Acoustics Experiment (ASIAEX SCS) in 2001 was used as a sound source to invert the geoacoustic parameters. The nearest horizontal distance between VLA and the passing ship was estimated by beamforming the receiving sounds on the array, and this distance was used in the sound propagation modal. In the modal, two layers structure were assumed for the bottom, so the sound speed (C1) and density (£l1) of sediment layer, sound speed (C2 ) and density (£l2) of subbottom layer, and total absorption coefficient (£\) need to be inverted. Matched field processing is used to solve this inverse problem, and computing the minimum cost function between the measured and modeled sound field, the best matched bottom parameters are C1¡×1600 m/s¡BC2¡×1650 m/s¡B£l1=1.6 g/cm3¡B£l2=2.1 g/cm3¡B£\=0.6 dB/£f. These results were compared with chirp sonar survey in this area, and the agreement is satisfactory.

Originally developed in the 1970s for the optimal control of systems governed by partial differential equations, the adjoint method has found several successful applications, e.g., in meteorology with large-scale 3D or 4D atmospheric data assimilation schemes, for carbon cycle data assimilation in biogeochemistry and climate research, or in oceanographic modelling with efficient adjoint codes of ocean general circulation models. Despite the variety of applications in these research fields, adjoint methods have only very recently drawn attention from the ocean acoustics community. In ocean acoustic tomography and geoacoustic inversion, where the inverse problem is to recover unknown acoustic properties of the water column and the seabed from acoustic transmission data, the solution approaches are typically based on travel time inversion or standard matched-field processing in combination with metaheuristics for global optimization. In order to complement the adjoint schemes already in use in meteorology and oceanography with an ocean acoustic component, this thesis is concerned with the development of the adjoint of a full-field acoustic propagation model for shallow water environments. In view of the increasing importance of global ocean observing systems such as the European Seas Observatory Network, the Arctic Ocean Observing System and Maritime Rapid Environmental Assessment (MREA) systems for defence and security applications, the adjoint of an ocean acoustic propagation model can become an integral part of a coupled oceanographic and acoustic data assimilation scheme in the future. Given the acoustic pressure field measured on a vertical hydrophone array and a modelled replica field that is calculated for a specific parametrization of the environment, the developed adjoint model backpropagates the mismatch (residual) between the measured and predicted field from the receiver array towards the source. The backpropagated error field is then converted into an estimate of the exact gradient of the objective function with respect to any of the relevant physical parameters of the environment including the sound speed structure in the water column and densities, compressional/shear sound speeds, and attenuations of the sediment layers and the sub-bottom halfspace. The resulting environmental gradients can be used in combination with gradient descent methods such as conjugate gradient, or Newton-type optimization methods tolocate the error surface minimum via a series of iterations. This is particularly attractive for monitoring slowly varying environments, where the gradient information can be used to track the environmental parameters continuously over time and space. In shallow water environments, where an accurate treatment of the acoustic interaction with the bottom is of outmost importance for a correct prediction of the sound field, and field data are often recorded on non-fully populated arrays, there is an inherent need for observation over a broad range of frequencies. For this purpose, the adjoint-based approach is generalized for a joint optimization across multiple frequencies and special attention is devoted to regularization methods that incorporate additional information about the desired solution in order to stabilize the optimization process. Starting with an analytical formulation of the multiple-frequency adjoint approach for parabolic-type approximations, the adjoint method is progressively tailored in the course of the thesis towards a realistic wide-angle parabolic equation propagation model and the treatment of fully nonlocal impedance boundary conditions. A semi-automatic adjoint generation via modular graph approach enables the direct inversion of both the geoacoustic parameters embedded in the discrete nonlocal boundary condition and the acoustic properties of the water column. Several case studies based on environmental data obtained in Mediterranean shallow waters are used in the thesis to assess the capabilities of adjoint-based acoustic inversion for different experimental configurations, particularly taking into account sparse array geometries and partial depth coverage of the water column. The numerical implementation of the approach is found to be robust, provided that the initial guesses are not too far from the desired solution, and accurate, and converges in a small number of iterations. During the multi-frequency optimization process, the evolution of the control parameters displays a parameter hierarchy which clearly relates to the relative sensitivity of the acoustic pressure field to the physical parameters. The actual validation of the adjoint-generated environmental gradients for acoustic monitoring of a shallow water environment is based on acoustic and oceanographic data from the Yellow Shark '94 and the MREA '07 sea trials, conducted in the Tyrrhenian Sea, south of the island of Elba. Starting from an initial guess of the environmental control parameters, either obtained through acoustic inversion with global search or supported by archival in-situ data, the adjoint method provides an efficient means to adjust local changes with a couple of iterations and monitor the environmental properties over a series of inversions. In this thesis the adjoint-based approach is used, e.g., to fine-tune up to eight bottom geoacoustic parameters of a shallow-water environment and to track the time-varying sound speed profile in the water column. In the same way the approach can be extended to track the spatial water column and bottom structure using a mobile network of sparse arrays. Work is currently being focused on the inclusion of the adjoint approach into hybrid optimization schemes or ensemble predictions, as an essential building block in a combined ocean acoustic data assimilation framework and the subsequent validation of the acoustic monitoring capabilities with long-term experimental data in shallow water environments.

Approved for public release, distribution is unlimited / Linear sound sweeps from a towed J15-3 sound source were collected at a moored VLA hydrophone array in the South China Sea during the ASIAEX experiment in May 2001. Measured signals were filtered and pulse compressed. The processed data showed a high signal to noise ratio. Given an a priori chirp sonar survey, a two layer bottom "first guess" model was constructed. A broadband coupled-mode model was used to perform an exhaustive frequency variant sensitivity study of VLA pressures to changes in bottom properties as a basis for the geoacoustic inverse problem. Study results provided information on the observability of the various geoacoustic parameters and a procedure for the inversion. Matched field processing of the VLA data, using the same coupledmode model, was then performed to calculate ambiguity diagrams from which geoacoustic parameter estimates were obtained. Since VLA pressure fields were not sensitive to changes in the sediment attenuation coefficient, a matched field technique that correlated the slope of modeled transmission loss to the negative slope of 10log of the observed energy was performed in order to obtain estimates of the attenuation. These estimates showed a frequency dependent attenuation coefficient in the 50-600Hz frequency band. / Lieutenant, United States Navy

Single-beam echosounders are an inexpensive, practical and non-invasive means of remote sensing the seabed. Ideally, the common single-beam echosounder should be able to tell fishers, navigators, engineers and scientists what the seabed consists of in addition to water depth. Low-frequency underwater acoustic systems (<10 kHz) can do this in some circumstances, but are expensive, offer limited resolution and potentially hazardous to marine mammals. High-frequency systems, such as single and multibeam echosounders, are very effective at mapping bathymetry, but do not characterize the seabed directly. Instead, these systems divide the seabed into self-similar segments or classes, and then rely on ground-truth data (usually sediment grab samples) to assign seabed-type labels such as sand, etc., to the classes. However, inadequate and inaccurate ground-truth is a major problem. Single-beam seabed classification methods also suffer from a lack of discriminatory power and from artefacts such as water depth and seabed slope. The cause of these problems is that the methods lack a basis in physics and are mainly statistical. Then, the central objective in this dissertation is to develop physics-based methods to improve classification and to address the problem of ground-truth by inferring seabed characteristics directly from the acoustics. An overview of current methods is presented along with case studies of single-beam surveys to introduce the current seabed classification method called QTC VIEW™ and to identify specific problems. A physical basis is established in scattering and geometrical theories and observations of field and model data. This leads to new classification and characterization methods that overcome the shortcomings of current seabed classification methods. Advancements also include new physical models of echosounding. The new methods are presented, implemented and evaluated. Highlights of experimental results include a new testbed located in Patricia Bay, British Columbia. The testbed consists of exhaustive ground-truth, surveys and novel controlled experiments with various single-beam echosounders, ranging in frequency from 12 to 200 kHz. Simulated echo time series data from the numerical BORIS model and a new analytic model are used to augment the testbed. Evaluation of experimental results shows the new physics-based methodology improves seabed classification significantly and enables seabed characterization by an uncalibrated single-beam echosounder. / Graduate

In shallow water environments, sound propagation experiences multiple interactions with the surface/bottom interfaces, with hydrodynamic disturbances such as internal waves, and with tides and fronts. It is thus very difficult to make satisfactory predictions of sound propagation in shallow water. Given that many of the ocean characteristics can be modeled as stochastic processes, the statistical measure, spatial coherence, is consequently an important quantity. Spatial coherence provides valuable information for array performance predictions. However, for the case of long-range, low frequency propagation, studies of spatial coherence influenced by various environmental parameters are limited insofar as having the appropriate environmental data with which to model and interpret the results. The comprehensive Asian Seas International Experiment 2001 (ASIAEX01) examined acoustic propagation and scattering in shallow water. Environmental oceanographic data were taken simultaneously with the acoustic data. ASIAEX01 provided a unique data set which enabled separate study of the characteristics of the oceanographic features and their influence on long range sound propagation. In this thesis, the environmental descriptors considered include sediment sound speed and attenuation, background internal waves, episodic non-linear internal waves, and air-sea interface conditions. Using this environmental data, the acoustic data are analyzed to show the characteristics of spatial coherence in a shallow water waveguide. It is shown that spatial coherence can be used as an inversion parameter to extract geoacoustic information for the seabed. Environmental phenomena including internal waves and wind-generated surface waves are also studied. The spatial and temporal variations in the sound field induced by them are presented. In addition, a tank experiment is presented which simulates propagation in a shallow water waveguide over a short range. Based on the data model comparison results, the model proposed here is effective in addressing the major environmental effects on sound propagation in shallow water.

The objective of this thesis is to develop and implement an algorithm for inverting the sound speed profile via estimation of the parameters embedded in a geoacoustic model. The environmental model inscribes a continuously-varying marine sediment layer with density and sound speed distributions represented by the generalized-exponential and inverse-square functions, respectively. Based upon a forward problem of plane-wave reflection from a non-uniform sediment layer overlying a uniform elastic basement, an inversion procedure for estimating the sound speed profile from the reflected sound field under the influence of noise is established and numerically implemented. The inversion invokes a probabilistic approach quantified by the posterior probability density for measuring the uncertainties of the estimated parameters from synthetic noisy data. Preliminary analysis on the solution of the forward problem and the sensitivity of the model parameters is first conducted, leading to a determination of the parameters chosen for inversion in the ensuing study. The parameter uncertainties referenced 1-D and 2-D marginal posterior probability densities are then examined, followed by the statistical estimation for the sound speed profile in terms of 99 % credibility interval. The effects of, the signal-to-noise ratio (SNR), the dimension of data vector, the region in which the data sampled, on the statistical estimation of sound speed profile are demonstrated and discussed.

The overall goal of this thesis is to develop non-linear Bayesian methods for three-dimensional tracking of a moving acoustic source in shallow water despite environmental uncertainty, with application to data from a horizontal line array (HLA) of hydrophones. As a precursor, Bayesian geoacoustic inversion is applied to estimate seabed model parameters and their uncertainties. A simulation study examines the effect of source and array factors on geoacoustic information content in matched-field inversion of HLA data, as quantified in terms of model parameter uncertainties. Bayesian geoacoustic inversion is applied to both controlled-source and ship-noise data from a HLA deployed on the seafloor in a shallow-water experiment conducted in the Barents Sea. A new approach is introduced to account for data error reduction due to averaging data over time-series subsegments (snapshots), based on empirically apportioning measurement and theory error, with effects on inversion results compared to those of existing approaches. It is further demonstrated that combining data from multiple, independent time-series segments (for a moving source) in the inversion can significantly reduce geoacoustic parameter uncertainties. Geoacoustic uncertainties are also shown to depend on ship range and orientation, with lowest uncertainties for short ranges and for the ship stern/propeller oriented toward the array. Sediment sound-speed profile and density estimates from controlled-source and ship-noise data inversions are found to be in good agreement with values from geophysical measurements. Two non-linear Bayesian matched-field inversion approaches are developed for three-dimensional source tracking despite environmental uncertainty. Focalization-tracking maximizes the posterior probability density (PPD) over track and environmental parameters. Synthetic test cases show that the algorithm substantially outperforms tracking with poor environmental estimates and generally obtains results close to those achieved with exact environmental knowledge. Marginalization-tracking integrates the PPD over environmental parameters to obtain joint marginal distributions over source coordinates, from which track uncertainty estimates and the most probable track are extracted. Both approaches are applied to data from the Barents Sea experiment. Focalization-tracking successfully estimates the tracks of the towed source and a surface ship in cases where simpler tracking algorithms fail. Marginalization-tracking generally outperforms focalization-tracking and gives uncertainty estimates that encompass the true tracks.