Wireless sensor networks and data fusion has received increasing attention in recent years, due to the ever increasing computational power, battery and wireless technology, and proliferation of sensor modalities. Notably, the application of acoustic sensors and arrays of sensors has expanded to encompass surveillance, teleconferencing, and sound source localization in adverse environments. The ability to passively locate and track acoustic sources, be they gunfire, animals, or geological events, is crucial to a wide range of applications. The challenge addressed herein is how to best utilize the massive amount of data collected from spatially distributed sensors. Localization in two acoustic propagation scenarios is addressed: the free-field assumption and the general case. In both cases, it is found that performance is highly dependent on the array-source geometry which in turn drives the design of localization strategies. First, the general surveillance problem including signal detection, classification, data association, localization and tracking is studied. Signal detectors are designed with a focus on robustness and capacity for real time implementation. Specifics of the data association problem relevant to acoustic measurements are addressed. Assuming free-field propagation, a localization algorithm is developed to harness some of the vast potential and robust nature of a sensor networks. In addition, a prototypical sensor network has been constructed to accompany the theoretical development, address real world situations, and demonstrate applicability. Experimental results obtained confirm the practicality of theoretical models, support numerical results, and illustrate the effectiveness of the proposed strategies and the system as a whole. In many situations of interest, obstacles to wave propagation such as terrain or buildings exist that provide unique challenges to localization. These obstacles introduce multiple paths, diffraction, and scattering into the propagation. The second part of this dissertation investigates localization in the general propagation scenario of a multi-wave, semi-reverberant environment characteristic of urban areas. Matched field processing is introduced as a feasible method and found to offer superior performance and flexibility over time reversal techniques. The effects of uncertainty in model parameters are studied in an urban setting. Multiarray processing methods are developed and strategies to mitigate the effects of model mismatch are established. / Ph. D.

<p>Two methods for evaluating and improving plane wave beamforming have beendeveloped. The methods estimate the shape of the wavefront and use theinformation in the beamforming. One of the methods uses estimates of the timedelays between the sensors to approximate the shape of the wavefront, and theother estimates the wavefront by matching the received wavefront to sphericalwavefronts of different radii. The methods are compared to a third more commonmethod of beamforming, which assumes that the impinging wave is planar. Themethods’ passive ranging abilities are also evaluated, and compared to a referencemethod based on triangulation.Both methods were evaluated with both real and simulated data. The simulateddata was obtained using Raylab, which is a simulation program based on ray-tracing. The real data was obtained through a field-test performed in the Balticsea using a towed array sonar and a stationary source emitted tones.The performance of the matched beamformers depends on the distance to the tar-get. At a distance of 600 m near broadside the power received by the beamformerincreases by 0.5-1 dB compared to the plane wave beamformer. At a distance of300 m near broadside the improvement is approximately 2 dB. In general, obtain-ing an accurate distance estimation proved to be difficult, and highly dependenton the noise present in the environment. A moving target at a distance of 600 mat broadside can be estimated with a maximum error of 150 m, when recursiveupdating of the covariance matrix with a updating constant of 0.25 is used. Whenrecursive updating is not used the margin of error increases to 400 m.</p>

Two methods for evaluating and improving plane wave beamforming have beendeveloped. The methods estimate the shape of the wavefront and use theinformation in the beamforming. One of the methods uses estimates of the timedelays between the sensors to approximate the shape of the wavefront, and theother estimates the wavefront by matching the received wavefront to sphericalwavefronts of different radii. The methods are compared to a third more commonmethod of beamforming, which assumes that the impinging wave is planar. Themethods’ passive ranging abilities are also evaluated, and compared to a referencemethod based on triangulation.Both methods were evaluated with both real and simulated data. The simulateddata was obtained using Raylab, which is a simulation program based on ray-tracing. The real data was obtained through a field-test performed in the Balticsea using a towed array sonar and a stationary source emitted tones.The performance of the matched beamformers depends on the distance to the tar-get. At a distance of 600 m near broadside the power received by the beamformerincreases by 0.5-1 dB compared to the plane wave beamformer. At a distance of300 m near broadside the improvement is approximately 2 dB. In general, obtain-ing an accurate distance estimation proved to be difficult, and highly dependenton the noise present in the environment. A moving target at a distance of 600 mat broadside can be estimated with a maximum error of 150 m, when recursiveupdating of the covariance matrix with a updating constant of 0.25 is used. Whenrecursive updating is not used the margin of error increases to 400 m.

No description available.

Within the last decade, a new type of signal acquisition has emerged called Compressive Sensing that has proven especially useful in providing a recoverable representation of sparse signals. This thesis presents similar results for Compressive Parametric Estimation. Here, signals known to lie on some unknown parameterized subspace may be recovered via randomized compressive measurements, provided the number of compressive measurements is a small factor above the product of the parametric dimension with the subspace dimension with an additional logarithmic term. In addition to potential applications that simplify the acquisition hardware, there is also the potential to reduce the computational burden in other applications, and we explore one such application in depth in this thesis. Source localization by matched-field processing (MFP) generally involves solving a number of computationally intensive partial differential equations. We introduce a technique that mitigates this computational workload by ``compressing'' these computations. Drawing on key concepts from the recently developed field of compressed sensing, we show how a low-dimensional proxy for the Green's function can be constructed by backpropagating a small set of random receiver vectors. Then, the source can be located by performing a number of ``short'' correlations between this proxy and the projection of the recorded acoustic data in the compressed space. Numerical experiments in a Pekeris ocean waveguide are presented which demonstrate that this compressed version of MFP is as effective as traditional MFP even when the compression is significant. The results are particularly promising in the broadband regime where using as few as two random backpropagations per frequency performs almost as well as the traditional broadband MFP, but with the added benefit of generic applicability. That is, the computationally intensive backpropagations may be computed offline independently from the received signals, and may be reused to locate any source within the search grid area. This thesis also introduces a round-robin approach for multi-source localization based on Matched-Field Processing. Each new source location is estimated from the ambiguity function after nulling from the data vector the current source location estimates using a robust projection matrix. This projection matrix effectively minimizes mean-square energy near current source location estimates subject to a rank constraint that prevents excessive interference with sources outside of these neighborhoods. Numerical simulations are presented for multiple sources transmitting through a generic Pekeris ocean waveguide that illustrate the performance of the proposed approach which compares favorably against other previously published approaches. Furthermore, the efficacy with which randomized back-propagations may also be incorporated for computational advantage (as in the case of compressive parametric estimation) is also presented.

Le geyser d'Old Faithful dans le Parc National de Yellowstone, aux États-Unis, est l'undes geysers les plus connus au monde. La cyclicité de ses éruptions est étudiée depuis lesannées 60 a_n de comprendre sa dynamique. En e_et, le caractère bimodal de la fréquencede ses éruptions intriguent les scienti_ques qui cherchent à en connaître les causes.Les enregistrements sismiques réalisés à la surface du geyser démontrent des signauximpulsionnels dont l'origine fut identi_ée par Sharon Kedar. Ainsi, en 1992, S. Kedar etses collègues ont déployé plusieurs capteurs sismiques dans le but d'étudier la source dessignaux sismiques de type tremor enregistrés à la surface du dôme. Ils ont ainsi identi_éla source du signal sismique enregistré à la surface du geyser comme étant des signauxde cavitation de bulles. La cavitation se produisant à la surface du niveau de l'eau dansle conduit, les localisations des sources sismiques réalisées à partir des enregistrements desurface peuvent être reliées au niveau de l'eau dans le conduit.Dans un premier temps nous avons proposé de localiser les sources sismiques desenregistrements à partir de la méthode du Matched Field Processing (MFP) provenantde l'acoustique sous-marine. Plusieurs algorithmes du MFP ont été testés pour pouvoirlocaliser au mieux les sources sismiques. La bonne concordance des résultats obtenus avecchacun des algorithmes a permis d'obtenir un grand nombre de localisations des sourcesau cours du cycle. Les positions déterminées avec les di_érents algorithmes du MFP ontpermis de mettre en évidence deux zones d'activité hydrothermale du geyser associéesà di_érentes périodes du cycle éruptif, telles que le remplissage du conduit avant leséruptions et l'alimentation du geyser en eau une fois la vidange du conduit e_ectuée.Dans un second temps, l'analyse des variations de vitesse des signaux sismiques estproposée pour suivre des changements des propriétés du dôme du geyser, comme des variationsde pression avant l'éruption. Pour cela, une nouvelle méthode basée sur les mesuresde phases instantanées est suggérée. Les résultats obtenus montrent des faibles changementsde vitesse, pouvant être associés à la mise en pression du dôme ou à l'augmentationde la température du milieu avant l'éruption en surface.

In this thesis, acoustic inversion methods are employed to estimate array element locations and the geoacoustic properties of the seabed using measured acoustic data consisting of noise from a surface ship in the Gulf of Mexico. The array element localization utilizes relative travel-time information obtained by cross-correlating the recorded time series of ship noise received at spatially separated hydrophones. The relative travel-time data are used in an inversion, based on the regularized least-squares method and the acoustic ray tracing equations, to obtain improved estimates of the receiver and source positions and their uncertainties. Optimization and Bayesian matched-field inversion methods are employed to estimate seabed geoacoustic properties and their uncertainties in the vicinity of a bottom-moored vertical line array using the recorded surface ship noise. This study is used to test the feasibility of matched-field methods to detect temporal changes in the geoacoustic properties of the seabed near a known gas hydrate mound in the Gulf of Mexico. Finally, a synthetic study is performed that demonstrates how ignoring environmental range dependence of seabed sound speed and water depth in matched-field inversion can lead to biases in the estimated geoacoustic parameters. The study considers the distributions of optimal parameter estimates obtained from a large number of range-independent inversions of synthetic data generated for random range-dependent environments. Range-independent Bayesian inversions are also performed on selected data sets and the marginal parameter distributions are examined. Both hard- and soft-bottom environments are examined at a number of scales of variability in sound speed and water depth.

On s’intéresse dans ce travail à l’aspect tridimensionnel (3D) de la propagation sonore en milieux océaniques petits fonds dans le cadre des problèmes inverses. Les problèmes inverses en acoustique sous-marine se basent sur la modélisation bidimensionnelle (2D) de la propagation, ignorant ainsi les effets de réfraction horizontale, qualifiés d’effets 3D. Toutefois, la propagation acoustique en environnements petits fonds, tels le plateau continental, peut être affectée par des effets 3D, leur prise en compte nécessitant l’utilisation de modèles pleinement 3D. Une inversion basée sur un modèle 3D devient inabordable pour plus de deux paramètres à la fois en raison de temps CPU particulièrement élevés. L’objectif de ce travail est d’examiner l’importance des effets 3D sur la performance et la fiabilité des procédures d’inversion habituellement utilisées dans les problèmes de l’acoustique sous-marine. Pour cela, on se place dans un guide d’onde océanique à géométrie inclinée. Des expérimentations à échelle réduite sont menées afin d’identifier et d’interpréter les effets 3D. Une procédure d’inversion par champs d’onde adaptés, formulée dans un cadre Bayesien et basée sur la recherche exhaustive dans l’espace des paramètres, est élaborée. L’inversion s’effectue en comparant des données basse fréquence du champ acoustique, recueillies le long d’antennes linéaires verticales ou horizontales, aux répliques générées par des modèles d’équation parabolique 2D et 3D. Les paramètres importants sont identifiés au moyen d’une étude de sensibilité de la fonction de coût. Dans une étape préliminaire, la performance de l’inversion est étudiée, sur données synthétiques bruitées, dans un cas simple permettant l’utilisation de modèles 2D. Une stratégied’inversion en sous-espaces résultant en une réduction importante des temps CPU pour l’inversion, est examinée. L’inversion est ensuite abordée en présence d’un fond incliné. La possibilité et les limites d’une inversion basée sur un modèle 2D sont explorées. Cette approche, mise en œuvre sur données synthétiques, met en évidence la pertinence de l’utilisation de modèles 2D en champ relativement proche. Une inversion basée sur un modèle 3D n’étant alors nécessaire que pour la pente, des temps CPU raisonnables sont ainsi réalisés. En revanche, en champ lointain, nous sommes confrontés à un risque potentiel d’estimation erronée et le recours à une modélisation 3D devient nécessaire. / This work deals with the three-dimensional (3D) aspect of sound propagation in shallow-water oceanic environments with respect to inverse problems. Inverse problems in underwater acoustics are based on twodimensional (2D) modeling of sound propagation, hence ignoring the effects of horizontal refraction, referred to as 3D propagation effects. However, the acoustic propagation in shallow-water environments, like the continental shelf, may be affected by 3D effects requiring 3D modeling to be accounted for. An inversion based on a 3D model for more than two parameters at a time becomes prohibitive due to dramatically increased CPU times. The aim of this work is to investigate the importance of the 3D effects with respect to the performance and reliability of the inversion procedures typically applied in problems of underwater acoustics. To this aim, we focus on a wedge-shaped oceanic wave guide. Laboratory scale experiments of long-range acoustic propagation are performed to identify and interpret the 3D effects due to a sloping bottom, as predicted by numerical simulations. A matched-field inversion procedure implemented within a Bayesian framework and based on the exhaustive search over the parameter space is elaborated. The inversion is performed by comparing low frequency acoustic field data, collected along vertical or horizontal line arrays, to replica generated from 2D and 3D parabolic equation codes. The recoverable parameters are identified by means of a sensitivity study of the cost function. In a preliminary step, the inversion performance is investigated on noisy synthetic data in a simple waveguide where 2D codes apply. A ubspace inversion strategy providing significant reduction in CPU times is examined. The inversion in the presence of a sloping bottom is then considered. The feasibility and the limits of an inversion matching replica from a 2D code are explored. This approach, applied on synthetic data, highlights the relevance of using 2D codes at relatively short ranges. An inversion based on a 3D code is thus only needed for the slope, and reasonable CPU times are achieved. On the other hand, important mismatch might occur at farther ranges and 3D modeling is required.