The single hydrophone localization problem is considered. Single hydrophone localization is a special case of matched field localization where measurements from only one hydrophone are available. The time series of the pressure at the hydrophone is compared with predicted times series calculated using an ocean acoustic propagation model for many different source locations. The source location that gives the best match between the predicted time series and the measurement is assumed to be the correct source location. Single hydrophone localization algorithms from the literature are reviewed and a new algorithm is introduced. The new algorithm does not require knowledge of the source signal and does not assume the use of a particular ocean acoustic model, unlike some algorithms in the literature. Source location estimates calculated from the new algorithm are compared with ground truth using simulated ocean acoustic measurements and experimental measurements. Source location estimates calculated using other algorithms from the literature are shown for comparison. The simulated measurements use three source signals with bandwidths of 10 Hz, 100 Hz, and 200 Hz and the ocean is modeled as a Pekeris waveguide. The new algorithm estimates the source location accurately for all three source signals when several of the localization algorithms from the literature give inaccurate estimates. Gaussian white noise signals are added to the measured signals to test the impact of signal-to-noise ratio (SNR) on the algorithm. Four signal-to-noise ratios of 60 dB, 40 dB, 20 dB, and 0 dB are used. The new algorithm gives accurate source location estimates down to an SNR of 20 dB for two of the source signal bandwidths. Source location estimates using other algorithms from the literature break down at either 20 dB or 0 dB. Source location estimates are calculated using two hydrophone measurements taken at different depths in an experiment conducted near the Bahamas. The new algorithm accurately estimates the source location in both cases. In one case, only two other localization algorithms from the literature locate the source accurately. In the other case, only one other localization algorithm succeeds.

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.

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. / The geyser of Old Faithful in the National Park of Yellowstone, in USA, is one of themost famous geysers in the world. The cyclic behavior of the geyser is studied since the60's with the aim to understand its dynamics. In fact, the bimodal nature of the frequencyof the eruptions raises questions and scientists want to know the causes of this behavior.The seismic signals recorded at the surface of the geyser present pulses whose origin wasidenti_ed by Sharon Kedar. Thus, in 1992, S. Kedar and his colleagues deployed severalseismic sensors in order to study the source of the seismic signals, which are tremor-like,recorded at the surface of the edi_ce. They identi_ed the source of the seismic signalrecorded at the surface of the geyser that they related to bubbles collapse. The bubblescollapse takes place at the surface of the water level in the conduit, thus the localizationsof the seismic sources determined with the records made at the surface would be relatedto the water level in the conduit.In a _rst time we proposed to locate the seismic sources of the records using theMatched Field Processing (MFP), a method used in ocean acoustics. Several algorithmsof the MFP were tested to better localize the seismic sources. The good agreement ofthe di_erent results obtained with each technique allowed to obtain a big number oflocalizations of the sources through the cycle. The locations determined with di_erentalgorithms of MFP allowed to highlight two areas of hydrothermal activities of the geyserlinked to di_erent periods of the eruption's cycle, as the _lling-up of the conduit beforeeruptions and the feeding of the geyser with water once the discharge of the conduitaccomplished.In a second time, the analysis of velocity's changes of the seismic records is proposedto follow changes in the properties of the edi_ce of the geyser, and pressure changes beforean eruption for example. To do that, a new technique based on the measurement of theinstantaneous phases is suggested. The results obtained show weak changes of velocity,that can be related to the pressure buildup of the edi_ce or to the increase of temperaturein the medium before an eruption.

In this thesis, localization of the underwater sound sources using matched field processing technique is considered. Localization of the underwater sound sources is one of the most important problems encountered in underwater acoustics and signal processing. Many techniques were developed to localize sources in range, depth and bearing angle. However, most of these techniques do not consider or only slightly takes into account the environmental factors that dramatically effect the propagation of underwater sound. Matched field processing has been developed as a technique that fully considers the environmental factors. Matched field processing has proven to be successful in many applications such as localization of sources in range and depth, the determination of environmental parameters, and the evaluation of model accuracies. In this study, first a comparative analysis of narrowband matched field processors is given. Namely four main processors: Bartlett processor, Minimum Variance Distortionless Response (MVDR) processor, MVDR with neighboring location constraints and MVDR with environmental perturbation constraints are compared in terms of their probability of correct localization under certain environmental conditions. Secondly, a performance assesment for the most common broadband matched field processors is made. The correct localization performances for incoherent broadband matched field processor, Tolstoy/Michalopoulo&#039 / s coherent matched field processor and broadband matched field processor with environmental perturbation constraints is given for certain environmental conditions. Finally, a new weighting approach to combine data for broadband matched field processing is introduced. The fact that information from different frequencies may have different reliability depending on the environmental conditions is considered to develop a weighting scheme. It is shown that a performance gain compared to existing processors can be achieved by using the weighting scheme introduced in this study.

Shallow water acoustics is one of the most challenging areas of underwater acoustics; it deals with strong sea bottom and surface interactions, multipath propagation, and it often involves complex variability in the water column. The sea bottom is the dominant environmental influence in shallow water. An accurate solution to the Helmholtz equation in a shallow water waveguide requires accurate seabed acoustic parameters (including seabed sound speed and attenuation) to define the bottom boundary condition. Direct measurement of these bottom acoustic parameters is excessively time consuming, expensive, and spatially limited. Thus, inverted geo-acoustic parameters from acoustic field measurements are desirable. Because of the lack of convincing experimental data, the frequency dependence of attenuation in sandy bottoms at low frequencies is still an open question in the ocean acoustics community. In this thesis, geo-acoustic parameters are inverted by matching different characteristics of a measured sound field with those of a simulated sound field. The inverted seabed acoustic parameters are obtained from long range broadband acoustic measurements in the Yellow Sea '96 experiment and the Shallow Water '06 experiment using the data-derived mode shape, measured modal attenuation coefficients, measured modal arrival times, measured modal amplitude ratios, measured spatial coherence, and transmission loss data. These inverted results can be used to test the validity of many seabed geo-acoustic models (including Hamilton model and Biot-Stoll model) in sandy bottoms at low frequencies. Based on the experimental results in this thesis, the non-linear frequency dependence of seabed effective attenuation is justified.

The goal of this thesis is to introduce new matched field processors (MFPs) for estimating the source location and the environmental parameters of a shallow water waveguide in which the source transmits either broadband or narrowband random signals.

The goal of this thesis is to introduce new matched field processors (MFPs) for estimating the source location and the environmental parameters of a shallow water waveguide in which the source transmits either broadband or narrowband random signals.

The detection and localization of important acoustic events in a complex urban environment, such as gunfire and explosions, is critical to providing effective surveillance of military and civilian areas and installations. In a complex environment, obstacles such as terrain or buildings introduce multipath propagations, reflections, and diffractions which make source localization challenging. This dissertation focuses on the problem of source localization in three-dimensional (3D) realistic urban environments. Two different localization techniques are developed to solve this problem: a) Beamforming using a few microphone phased arrays in conjunction with a high fidelity model and b) Fingerprinting using many dispersed microphones in conjunction with a low fidelity model of the environment. For an effective source localization technique using microphone phased arrays, several candidate beamformers are investigated using 2D and corresponding 3D numerical models. Among them, the most promising beamformers are chosen for further investigation using 3D large models. For realistic validation, localization error of the beamformers is analyzed for different levels of uncorrelated noise in the environment. Multiple-array processing is also considered to improve the overall localization performance. The sensitivity of the beamformers to uncertainties that cannot be easily accounted for (e.g. temperature gradient and unmodeled object) is then investigated. It is observed that evaluation in 3D models is critical to assess correctly the potential of the localization technique. The enhanced minimum variance distortionless response (EMVDR) is identified to be the only beamformer that has super-directivity property (i.e. accurate localization capability) and still robust to uncorrelated noise in the environment. It is also demonstrated that the detrimental effect of uncertainties in the modeling of the environment can be alleviated by incoherent multiple arrays. For efficient source localization technique using dispersed microphones in the environment, acoustic fingerprinting in conjunction with a diffused-based energy model is developed as an alternative to the beamforming technique. This approach is much simpler requiring only microphones rather than arrays. Moreover, it does not require an accurate modeling of the acoustic environment. The approach is validated using the 3D large models. The relationship between the localization accuracy and the number of dispersed microphones is investigated. The effect of the accuracy of the model is also addressed. The results show a progressive improvement in the source localization capabilities as the number of microphones increases. Moreover, it is shown that the fingerprints do not need to be very accurate for successful localization if enough microphones are dispersed in the environment. / Ph. D.

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.

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.