Recent theoretical and experimental studies have demonstrated that an estimate of the Green's function between two hydrophones can be extracted passively from the cross‐correlation of ambient noise recorded at these two points. Hence monitoring the temporal evolution of these estimated Green's functions can provide a means for noise‐based acoustic tomography using a distributed sensor network. However, obtaining unbiased Green's function estimate requires a sufficiently spatially and temporally diffuse ambient noise field. Broadband ambient noise ([200 Hz-20 kHz]) was recorded continuously for 2 days during the SWAMSI09 experiment (next to Panama City, FL) using two moored vertical line arrays (VLAs) spanning 7.5m of the 20‐m water column and separated by 150 m. The feasibility of noise‐based acoustic tomography ([300-1000 Hz]) was assessed in this dynamic coastal environment over the whole recording period. Furthermore, coherent array processing of the computed ocean noise cross‐correlations between all pairwise combinations of hydrophones was used to separate acoustic variations between the VLAs caused by genuine environmental fluctuations-such as internal waves-from the apparent variations in the same coherent arrivals caused when the ambient noise field becomes strongly directional, e.g., due to an isolated ship passing in the vicinity of the VLAs.

Thesis (Ph. D.)--University of Washington, 1998. / Vita. Includes bibliographical references (leaves [112]-124).

Thesis (M.S.)--Joint Program in Oceanographic Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 1997. / Includes bibliographical references (p. 65-66). / The Surface Suspended Acoustic Receiver (SSAR) is a free-drifting platform intended for use as a receiver in large scale acoustic tomography experiments. Early prototypes of the SSAR exhibited very poor signal-to-noise ratios in the frequency band of the hydrophones. This thesis details efforts to reduce the hydrophone noise level by combining the analysis of experimental data with the results from numerical models. Experiments were conducted to quantify both the frequency content and magnitude of noise generated on the SSAR. Through a program of sea trials and pond testing, two noise sources were identified. The dominant source of noise in the SSAR is velocity dependent flow noise that results from turbulent pressure fluctuations on the hydrophones. A second noise source results from the acceleration sensitivity of the hydrophones in conjunction with high frequency accelerations present in the hydrophone array cable. These high frequency accelerations also show a velocity dependence. The presence of the acceleration-induced noise leads to correlations between the signals from adjacent hydrophones, thus distorting the typical picture that flow noise should be uncorrelated along an array. The primary methods of eliminating the noise are encapsulating the hydrophone in a flow shield, eliminating the array cable, and slowing the system down by replacing the wave following surface buoy with a spar buoy. Using the experimental results, empirical relationships between hydrophone velocity and expected noise level are formed for both shielded and unshielded hydrophones. The numerical models developed as a part of this effort are then used to predict the velocities for a wide range of possible SSAR configurations. The models can also provide information, such as system tensions, that is useful in evaluating the longevity and survivability of SSARs. Modeled design fixes include subsurface component changes as well as comparing a wave following surface buoy to a spar buoy. / by Jason I. Gobat. / M.S.

In marine environments, acoustic wave propagation is determined by sound-speed variations in the water column (related to salinity, temperature and pressure) ,and seafloor properties in shallow environments. The refraction index variations and the boundary conditions guide the wave propagation so that an important amount of acoustic energy can propagate over long distances. Measurements of acoustic transmissions coupled with propagation models can be inverted to infer the water column properties (tomography) and the seafloor and subseafloor properties (geoacoustics).<p><p>In this thesis a new method for shallow water inversion based on the sequential assimilation of acoustic measurements in Kalman filters is developed. Filtering algorithms for nonlinear systems, as the ensemble Kalman filter (EnKF), enable the integration of complex acoustic propagation models in the measurement model. The inverse problem is here reformulated into a state-space model to track sequentially the parameters (temperature, receiver positions, etc.) and their uncertainty by filtering regularly new acoustic data.<p><p>Different applications are proposed to demonstrate the sequential acoustic filtering approach. First, the problem of characterizing horizontal inhomogeneities in the sound-speed field between an acoustic source and a vertical array of receivers is addressed. Starting from a range-averaged sound-speed profile, the filtering of complex multifrequency data enables the estimate and tracking of the range-dependence of the sound-speed field.<p>The second application deals with the geoacoustic inversion problem based on a mobile source-receiver setup. The filtering approach is shown to provide more stable results than conventional inversion methods with a reduced computational burden. The last application is dedicated to the tracking of specific oceanic structures affecting the sound-speed field, here thermal fronts. An original parameterization scheme which is specific to the tracked feature is developed and enables to monitor the principal characteristics of the sound-speed field by filtering multifrequency acoustic data.<p><p>This work shows that the sequential filtering approach of transmitted acoustic data can lead to environmental estimates on spatial and temporal scale of interest for regional or coastal oceanographic models and can supplement the dataset assimilated nowadays for forecasting purposes./Dans les environnements marins, la propagation des ondes acoustiques est directement conditionnée par les variations de vitesse de propagation dans l'eau (liée à la température, la salinité et la pression hydrostatique), ainsi que les propriétés du fond, lorsque le milieu est peu profond. La propagation de ces ondes, typiquement guidée par les variations d'indice de réfraction et les conditions aux limites, permet de transmettre une quantité d'énergie acoustique importante sur de longues distances. Associées à des modèles de propagation, des mesures de transmission acoustique peuvent être inversées afin de déterminer les propriétés de l'environnement sondé, que ce soit de la colonne d'eau (tomographie) ou du fond marin (géoacoustique).<p><p>Dans cette thèse, une nouvelle méthode d'inversion en milieu peu profond, basée sur l'assimilation séquentielle de mesures acoustiques dans des filtres de Kalman, est développée. Les algorithmes de filtrage développés pour les systèmes non linéaires, tel que l'ensemble Kalman filter (EnKF), permettent d'intégrer des modèles de propagation acoustique complexes au sein du modèle de mesure. Le problème inverse est reformulé de façon séquentielle, en un modèle d'espace d'états, de sorte que l'évolution des paramètres (température, positions des récepteurs, etc.) et de leur incertitude est suivie au fur et à mesure de l'assimilation de nouvelles mesures.<p><p>Différentes applications sont proposées pour démontrer les performances du filtrage séquentiel. Le premier problème abordé est celui de l'inversion et du suivi des inhomogénéités horizontales du champ de vitesse entre une source acoustique et une antenne verticale de récepteurs. A partir d'un profil de vitesse moyen sur la distance source-récepteurs, le filtrage de mesures complexes multi-fréquences permet d'estimer la dépendance horizontale du champ de vitesse et son évolution au cours du temps. La nature séquentielle de l'algorithme de filtrage motive la seconde application, dédiée à l'estimation des paramètres géoacoustiques d'un environnement à partir d'une configuration source-récepteur mobile. Les résultats démontrent que l'approche par filtrage permet d'obtenir des estimations géoacoustiques plus stables que celles obtenues par les méthodes d'inversion conventionnelles avec un coût de calcul réduit. La troisième et dernière application est dédiée au suivi de structures océaniques marquées, tels que les fronts thermiques. Une paramétrisation originale spécifique à la structure inversée est proposée et permet d'estimer et de suivre les caractéristiques principales du champ de température par filtrage de données acoustiques multi-fréquences.<p><p>Ce travail montre que l'approche séquentielle de l'inversion des données acoustiques peut mener à des estimations environnementales sur des échelles spatiales et temporelles d'intérêt pour les modèles océanographiques côtiers et régionaux, de façon à compléter les données assimilées quotidiennement pour les prédictions. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

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.<p><p>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. <p><p>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. <p><p>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. <p><p>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.<p><p>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.<p><p>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.<p><p>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. <p><p>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.<p> <p>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. <p><p>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. <p><p>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.<p><p>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. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished