Underwater Object Tracking Using Time Frequency Signatures of Acoustic Signals

International audienceDetecting underwater objects is an important ap plication in marine applications. Most of the techniques are based on the amplitude related techniques, whereby the amplitude of the received echo is used to detect objects within specified bounds. Amplitude techniques however are prone to interference and attenuation, thus limiting the capabilities of such systems. Hence, the aim of this paper is to propose a new technique that detect and track underwater moving objects usingthe turbulence generated by the object. Wideband signals have proven to be a very efficient alternative for merging turbulent flow characteristics and waveform design in order to describe and explain the behavior of turbulence, both artificial and natural. Therefore, constructing adapted waveforms to the natural turbulence embedded in the flow, as well as to the artificial turbulence created by an unknown underwater moving object may hold the key for a new technique for underwater object tracking. When acoustic signals with a particular Instantaneous Frequency Law traveling into underwater environment will hit a moving object, their Instantaneous Frequency Law will capture the object's artificial turbulence, as well as the natural turbulence embedded in the flow. Experimental results carried out in our reduced scale facility provide the validation of the technique

Distributed Data Classification in Underwater Acoustic Sensors based on Local Time-Frequency Coherence Analysis

International audienceThis paper introduces a stochastic approach that considers the distributed classification problem for a network of underwater acoustic sensors. The proposed classifier applies the third order polynomial regression to the instantaneous frequency extracted from time-frequency representation of different classes of signals and represent the polynomial's coefficients in a threedimensional representation space. This automatic classifier is then compared to a non-parametric classifier based on the training of a standard neural network. The results of the proposed method on real data illustrate the efficiency of this algorithm, in terms of signal's characterization and lower communication bit rates between each sensor and the data center

On the vortex parameter estimation using wide band signals in active acoustic system

International audienceThis paper proposes a new method for detection of the vortex presence in fluid flow based on an active acoustic system. The experiment that validates the theory was done on a reduced scale facility using ultrasonic transceivers. The main objective was to highlight the effect of a cavitation vortex on an applied wide band signal. In order to accomplish that, the Recurrence Plot Analysis (RPA) was investigated which emhasizes similar states of a dynamic process. The Tests were done from no vortex cavitation flow to vortex cavitation flow and backward

Zernike ultrasonic tomography for fluid velocity imaging based on pipeline intrusive time-of-flight measurements

International audienceIn this paper, we propose a novel ultrasonic tomography method for pipeline flow field imaging, based on the Zernike polynomial series. Having intrusive multipath time-offlight ultrasonic measurements (difference in flight time and speed of ultrasound) at the input, we provide at the output tomograms of the fluid velocity components (axial, radial, and orthoradial velocity). Principally, by representing these velocities as Zernike polynomial series, we reduce the tomography problem to an ill-posed problem of finding the coefficients of the series, relying on the acquired ultrasonic measurements. Thereupon, this problem is treated by applying and comparing Tikhonov regularization and quadratically constrained l1 minimization. To enhance the comparative analysis, we additionally introduce sparsity, by employing SVD-based filtering in selecting Zernike polynomials which are to be included in the series. The first approach - Tikhonov regularisation without filtering, is used because it is the most suitable method. The performances are quantitatively tested by considering a residual norm and by estimating the flow using the axial velocity tomogram. Finally, the obtained results show the relative residual norm and the error in flow estimation, respectively, ~0.3% and ~1.6% for the less turbulent flow and ~0.5% and ~1.8% for the turbulent flow. Additionally, a qualitative validation is performed by proximate matching of the derived tomograms with a flow physical model

Développement d’indicateurs de la dynamique spatio-temporelle sédimentaire d’un cours d’eau mesurés par acoustique passive

This thesis deals with theoretical and experimental concepts of passive acoustic monitoring of sediment transport in rivers. Hence, the motivation is the use of hydrophones to sense the sound pressure generated by impacts between the sediments that are transported on the bed river. The technique is very cheap and easy to deploy on the field but it lacks of knowledge on the nature of the river soundscape’s acoustic sources. In order to separate the various types of noise sources composing the soundscape, a spectral analysis is frequently used to detect the bedload noise passband. The bedload spectral information is used in this thesis to estimate the transported, or bedload, grain size distribution. The study is based on the physical evidence of the existence of a dependency between the size of impacting particles and the frequency of the impacts. Therefore, the spatial and temporal dynamics of the bedload grain size distributions in gravel rivers will be assessed by developing acoustic spectra indexes.Firstly, the analytic solutions of hertzian impact between two rigid spheres and between a sphere and a slab are studied. The spectrum’s center and peak frequencies are most sensible on the grain size and then on the impact velocity. The analytic solutions and grain size distributions are used to model bedload acoustic spectra. Such model is sensible on the grain size distribution shape followed by the impact velocities of sediments. Its definition does not include non-linear transmission losses, i.e. attenuation with frequency due to scattering and absorption effects, and also the impact velocity is constant no matter the dimension of particles.Secondly, the bedload acoustic model is used for implementing inversion methods to estimate the grain size distributions. Such a method is defined in a least square algebraically framework, named the Non-Negative Least Square method, and uses analytical solutions of hertzian impacts to inverse the acoustic spectra. Field measurements on two large gravel rivers like Isère River, in Grenoble, France, and Drau River, at Dellach, in Austria, revealed coherent results as validated by physical sampling trials of bedload transport. It was observed a spatial variability in the estimated grain size distribution across the Isère River whereas a temporal variability was observed from the inversion of Drau River’s spectra.The previous bedload spectral model is enhanced by including concepts from the physics of fractional transport rate in gravel rivers, of particle saltation model and acoustic models of propagation. One can model acoustic maps of bedload noise from spatializing the impact rates at the reach scale. Here, the model is tests to localize the bedload noise in the Isère River’s cross-section by matching the measured spectra to the modeled ones. The acoustic maps obtained from this model are successfully predicted as validated by the measured maps in the Isère River in Grenoble.Cette thèse aborde le sujet du monitorage par acoustique passive dans les rivières pour la mesure du transport sédimentaire par charriage. La motivation de la recherche est l’utilisation d’hydrophones déployés dans un cours d’eau pour détecter et mesurer le bruit des sédiments transportés sur le fond de la rivière. La technique est très prometteuse grâce à la facilité de déploiement sur le terrain et aux coûts réduits mais elle est encore déficitaire en méthodologie sur la connaissance du bruit ambiant. Le bruit ambiant est un mélange de sources de bruit parmi lesquelles se trouve le bruit du transport par charriage des sédiments. La classification des bandes passantes des spectres acoustiques permet de séparer les différentes sources acoustiques. Dans cette thèse, on analyse la dynamique du charriage par l’analyse de la variabilité de la bande passante du charriage des spectres acoustiques. Cette variabilité peut être temporelle, sur des chroniques acoustiques, et spatiale sur des mesures en plusieurs points de la section de la rivière.La recherche commence par une analyse théorique sur les solutions analytiques des impacts hertziens entre deux sphères rigides ou entre une sphère et le fond considéré comme une plaque. La sensibilité des fréquences centrales et des pics spectraux est dominée premièrement par les dimensions des particules et secondement par la vitesse d’impact. La solution analytique est utilisée conjointement avec des distributions granulométriques pour définir un modèle linéaire d’addition des spectres. La forme du spectre ainsi modélisé dépend notamment par des caractéristiques statistiques de la distribution granulométrique et de la vitesse d’impact du modèle d’impact. Le modèle spectral est dans un état simplifié parce qu’on suppose une vitesse d’impact uniforme quelle que soit la dimension des particules en collision et également parce qu’on ne considère pas les effets de l’atténuation à cause de la diffusion ou l’absorption des ondes sonores.Le modèle spectral du charriage est utilisé par une méthode d’inversion des densités spectrales de puissances afin d’estimer la distribution granulométrique des sédiments transportés. La méthode d’inversion nommée « Non-Negative Least Square » est purement algébrique car elle est définie comme un problème au sens de moindres carrés avec une contrainte de positivité sur la solution. Les mesures sur deux rivières à graviers, Isère à Grenoble et la Drave, à Dellach en Autriche, donnent des résultats en concordance avec les mesures du transport sédimentaire. On a observé que l’inversion des spectres permet l’analyse de la dynamique des courbes granulométriques estimées tant spatiale (sur l’Isère à Grenoble) que temporelle (sur la Drave à Dellach).Le modèle de charriage est encore développé par l’intégration de la physique du transport sédimentaire, de l’hydraulique et de l’acoustique des impacts. Ce modèle vise l’analyse de spatialité et la temporalité des impacts dans une section de la rivière et donne une approche plus complète au modèle de charriage précédemment présenté. L’identification des spectres modélisés à des spectres simulés permet des modéliser les taux des impacts (et les flux sédimentaires) et la localisation de la bande principale de charriage dans la rivière de l’Isère à Grenoble

Measuring bedload grain-size distributions with passive acoustic measurements

Bedload Self-Generated Noise (SGN) measurements consist in deploying an underwater microphone (i.e. a hydrophone) in the water course and to record the ambient noise of a river. The use of hydrophones is of interest as it can be easily deployed and can provide a continuous monitoring of bedload transport. However, developments are still required to fully understand how bedload characteristics (e.g. specific flux or granulometry) are related to bedload SGN parameters (e.g. acoustic power and spectrum). Laboratory experiments have shown that central and peak frequencies of bedload noise decrease as the particle size increases, just like in string instruments where the tone frequency decreases from a narrow string to a broader string. In this paper, we propose to test a new inverse method enabling the estimation of bedload grain size distributions from SGN measurements. The inverse method is based on a theoretical modelling of the noise generated by a bedload mixture. SGN and physical sampling measurements have been made in 5 French alpine rivers having several transport conditions (bedload D50 from 1 to 40 mm) and varying slopes (0.05 to 1%). Measurements were made for specific bedload flux varying from 10 to 150 g.m-1s-1. The proposed inverse method was used to estimate the bedload grain size distributions. SGN results are compared to bedload samples and are found to largely overestimate sampled granulometries. Finally, it is observed that the spectral characteristics of bedload SGN are not related to bedload GSD but rather to the roughness of the river bed, acting as a source of attenuation and shaping bedload SGN spectra

Passive acoustic inversion to estimate bedload size distribution in rivers

International audienceThe main subject of our research is the analysis of quality of water in rivers by measuring the bedload transport. The bedload transport is defined by a particle moving close to the river bed, by sliding, saltation and rolling. We have adopted the Passive Acoustic Monitoring to listen to the river soundscape using a submerged hydrophone. These sources are due to surface waves, to turbulence and to inter-particular collisions. Inter-particular collision is the noise that we study because it is generated by the bedload phenomenon. In this study, we developed a Least Square procedure to inverse the spectra of noise recorded. The result represents an estimation of the transported grain size distribution

IoT Acoustic Antenna Development for Fish Biomass Long-Term Monitoring

International audienceThis paper proposes a novel Internet of Things (IoT) hardware framework for detecting and counting operations for fish biomass estimation. Based on a multi-static configuration, the core part of the system is using a single board computer with high capabilities in ADC and DAC and an analog multiplexer with a competitive switching rate

Inversion de Signaux d'Acoustique Passive pour Estimer la Granulométrie des Sédiments Transportés dans une Rivìère

National audienceLe contexte de notre contribution est la mesure par acoustique passive du transport sédimentaire dans les rivières. A partir d'une mesure du spectre acoustique des sons générés par les chocs entre particules sur le lit de la rivière, nous proposons un schéma d'inversion permettant d'estimer la granulométrie (i.e distribution des diamètres de particules mises en mouvement). Pour cela, nous modélisons le spectre acoustique comme la somme des spectres individuels des chocs obtenus pour un diamètre donné et pondérés par la proportion relative de chaque diamètre (i.e la granulométrie). L'estimation de la granulométrie est obtenue par une minimisation de l'erreur quadratique (E.Q) entre spectre mesuré et spectre modélisé. Une minimisation directe de l'E.Q produit une inversion instable puisque les spectres individuels des chocs ont des formes similaires. Ce problème inverse mal posé est régularisé en introduisant la contrainte de positivité de la granulométrie lors de la minimisation de l'E.Q. La méthode régularisée est comparée avec l'état de l'art sur des données simulées réalistes, elle améliore considérablement l'estimation de la granulométrie