92 research outputs found
Robust Adaptive Detection of Buried Pipes using GPR
International audienceDetection of buried objects such as pipes using a Ground Penetrating Radar (GPR) is intricate for three main reasons. First, noise is important in the resulting image because of the presence of several rocks and/or layers in the ground, highly influencing the Probability of False Alarm (PFA) level. Also, wave speed and object responses are unknown in the ground and depend on the relative permit-tivity, which is not directly measurable. Finally, the depth of the pipes leads to strong attenuation of the echoed signal, leading to poor SNR scenarios. In this paper, we propose a detection method: (1) enhancing the signal of interest while reducing the noise and layer contributions, and (2) giving a local estimate of the relative permittivity. We derive an adaptive detector where the signal of interest is parametrised by the wave speed in the ground. For this detector, noise is assumed to follow a Spherically Invariant Random Vector (SIRV) distribution in order to obtain a robust detection. We use robust maximum likelihood-type covariance matrix estimators called M-estimators. To handle the significant amount of data, we consider regularised versions of said estimators. Simulation will allow to estimate the relation PFA-Threshold. Comparison is performed with standard GPR processing methods, showing the aptitude of the method in detecting pipes having low response levels with a reasonable PFA
Framework for a Perceptive Mobile Network using Joint Communication and Radar Sensing
In this paper, we develop a framework for a novel perceptive mobile/cellular
network that integrates radar sensing function into the mobile communication
network. We propose a unified system platform that enables downlink and uplink
sensing, sharing the same transmitted signals with communications. We aim to
tackle the fundamental sensing parameter estimation problem in perceptive
mobile networks, by addressing two key challenges associated with sophisticated
mobile signals and rich multipath in mobile networks. To extract sensing
parameters from orthogonal frequency division multiple access (OFDMA) and
spatial division multiple access (SDMA) communication signals, we propose two
approaches to formulate it to problems that can be solved by compressive
sensing techniques. Most sensing algorithms have limits on the number of
multipath signals for their inputs. To reduce the multipath signals, as well as
removing unwanted clutter signals, we propose a background subtraction method
based on simple recursive computation, and provide a closed-form expression for
performance characterization. The effectiveness of these methods is validated
in simulations.Comment: 14 pages, 12 figures, Journal pape
Advanced Techniques for Ground Penetrating Radar Imaging
Ground penetrating radar (GPR) has become one of the key technologies in subsurface sensing and, in general, in non-destructive testing (NDT), since it is able to detect both metallic and nonmetallic targets. GPR for NDT has been successfully introduced in a wide range of sectors, such as mining and geology, glaciology, civil engineering and civil works, archaeology, and security and defense. In recent decades, improvements in georeferencing and positioning systems have enabled the introduction of synthetic aperture radar (SAR) techniques in GPR systems, yielding GPR–SAR systems capable of providing high-resolution microwave images. In parallel, the radiofrequency front-end of GPR systems has been optimized in terms of compactness (e.g., smaller Tx/Rx antennas) and cost. These advances, combined with improvements in autonomous platforms, such as unmanned terrestrial and aerial vehicles, have fostered new fields of application for GPR, where fast and reliable detection capabilities are demanded. In addition, processing techniques have been improved, taking advantage of the research conducted in related fields like inverse scattering and imaging. As a result, novel and robust algorithms have been developed for clutter reduction, automatic target recognition, and efficient processing of large sets of measurements to enable real-time imaging, among others. This Special Issue provides an overview of the state of the art in GPR imaging, focusing on the latest advances from both hardware and software perspectives
Blind source separation for clutter and noise suppression in ultrasound imaging:review for different applications
Blind source separation (BSS) refers to a number of signal processing techniques that decompose a signal into several 'source' signals. In recent years, BSS is increasingly employed for the suppression of clutter and noise in ultrasonic imaging. In particular, its ability to separate sources based on measures of independence rather than their temporal or spatial frequency content makes BSS a powerful filtering tool for data in which the desired and undesired signals overlap in the spectral domain. The purpose of this work was to review the existing BSS methods and their potential in ultrasound imaging. Furthermore, we tested and compared the effectiveness of these techniques in the field of contrast-ultrasound super-resolution, contrast quantification, and speckle tracking. For all applications, this was done in silico, in vitro, and in vivo. We found that the critical step in BSS filtering is the identification of components containing the desired signal and highlighted the value of a priori domain knowledge to define effective criteria for signal component selection
Caractérisation de vortex intraventriculaires par échographie Doppler ultrarapide
Les maladies cardiaques sont une cause majeure de mortalité dans le monde (la première
cause en Amérique du nord [192]), et la prise en charge de ses maladies entraîne des coûts
élevés pour la société. La prévalence de l’insuffisance cardiaque augmente fortement avec
l’âge, et, avec une population vieillissante, elle va demeurer une préoccupation croissante dans
le futur, non seulement pour les pays industrialisés mais aussi pour ceux en développement.
Ainsi il est important d’avoir une bonne compréhension de son mécanisme pour obtenir
des diagnostics précoces et un meilleur prognostic pour les patients. Parmi les différentes
formes d’insuffisance cardiaque, on trouve la dysfonction diastolique qui se traduit par une
déficience du remplissage du ventricule. Pour une meilleure compréhension de ce mécanisme,
de nombreuses études se sont intéressées au mouvement du sang dans le ventricule. On sait
notamment qu’au début de la diastole le flux entrant prend la forme d’un anneau vortical (ou
vortex ring). La formation d’un vortex ring par le flux sanguin après le passage d’une valve a
été décrite pour la première fois en 1513 par Léonard de Vinci (Fig. 0.1). En effet après avoir
moulé l’aorte dans du verre et ajouter des graines pour observer le flux se déplaçant dans son
fantôme, il a décrit l’apparition du vortex au passage de la valve aortique. Ces travaux ont pu
être confirmés 500 ans plus tard avec l’apparition de l’IRM [66]. Dans le ventricule, le même
phénomène se produit après la valve mitrale, c’est ce qu’on appelle le vortex diastolique. Or,
le mouvement d’un fluide (ici le sang) est directement relié a son environnement : la forme
du ventricule, la forme de la valve, la rigidité des parois... L’intérêt est donc grandissant
pour étudier de manière plus approfondie ce vortex diastolique qui pourrait apporter de
précieuses informations sur la fonction diastolique. Les modalités d’imagerie permettant de
le visualiser sont l’IRM et l’échographie. Cette thèse présente l’ensemble des travaux effectués
pour permettre une meilleure caractérisation du vortex diastolique dans le ventricule gauche
par imagerie ultrasonore Doppler. Pour suivre la dynamique de ce vortex dans le temps, il
est important d’obtenir une bonne résolution temporelle. En effet, la diastole ventriculaire
dure en moyenne 0.5 s pour un coeur humain au repos, une cadence élevée est donc essentielle
pour suivre les différentes étapes de la diastole. La qualité des signaux Doppler est également
primordiale pour obtenir une bonne estimation des vitesses du flux sanguin dans le ventricule.
Pour étudier ce vortex, nous nous sommes intéressés à la mesure de sa vorticité en son centre
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et à l’évolution de cette dernière dans le temps. Le travail se divise ainsi en trois parties,
pour chaque un article a été rédigé :
1. Développement d’une séquence Doppler ultrarapide : La séquence se base sur l’utilisation
d’ondes divergentes qui permettent d’atteindre une cadence d’image élevée.
Associée à la vortographie, une méthode pour localiser le centre du vortex diastolique
et en déduire sa vorticité, nous avons pu suivre la dynamique de la vorticité
dans le temps. Cette séquence a permis d’établir une preuve de concept grâce à des
acquisitions in vitro et in vivo sur des sujets humains volontaires.
2. Développement d’une séquence triplex : En se basant sur la séquence ultrarapide Doppler,
on cherche ici à ajouter des informations supplémentaires, notamment sur le
mouvement des parois. La séquence triplex permet non seulement de récupérer le
mouvement sanguin avec une haute cadence d’images mais aussi le Doppler tissulaire.
Au final, nous avons pu déduire les Doppler couleur, tissulaire, et spectral, en plus
d’un Bmode de qualité grâce à la compensation de mouvement. On peut alors observer
l’interdépendance entre la dynamique du vortex et celle des parois, en récupérant
tous les indices nécessaires sur le même cycle cardiaque avec une acquisition unique.
3. Développement d’un filtre automatique : La quantification de la vorticité dépend
directement des vitesses estimées par le Doppler. Or, en raison de leur faible
amplitude, les signaux sanguins doivent être filtrés. En effet lors de l’acquisition les
signaux sont en fait une addition des signaux sanguins et tissulaires. Le filtrage est
une étape essentielle pour une estimation précise et non biaisée de la vitesse. La
dernière partie de ce doctorat s’est donc concentrée sur la mise au point d’un filtre
performant qui se base sur les dimensions spatiales et temporelles des acquisitions.
On effectue ainsi un filtrage du tissu mais aussi du bruit. Une attention particulière
a été portée à l’automatisation de ce filtre avec l’utilisation de critères d’information
qui se basent sur la théorie de l’information.Heart disease is one of the leading causes of death in the world (first cause in North America
[192]), and causes high health care costs for society. The prevalence of heart failure increases
dramatically with age and, due to the ageing of the population, will remain a major concern in
the future, not only for developed countries, but also for developing countries. It is therefore
crucial to have a good understanding of its mechanism to obtain an early diagnosis and a
better prognosis for patients. Diastolic dysfunction is one of the variations of heart failure
and leads to insufficient filling of the ventricle. To better understand the dysfunction, several
studies have examined the blood motion in the ventricle. It is known that at the beginning of
diastole, the filling flow creates a vortex pattern known as a vortex ring. This development of
the ring by blood flow after passage through a valve was first described in 1513 by Leonardo
Da Vinci (Fig. 0.1). After molding a glass phantom in an aorta and adding seeds to visually
observe the flow through the phantom, he could describe the vortex ring development of
the blood coming out of the aortic valve. His work was confirmed 500 years later with the
emergence of MRI [66]. The same pattern can be observed in the left ventricle when the flow
emerges from the mitral valve, referred to as the diastolic vortex. The flow motion (in our
case the blood) is directly related to its environment : shape of the ventricle, shape of the
valve, stiffness of the walls... There is therefore a growing interest in further studies on this
diastolic vortex that could lead to valuable information on diastolic function. The imaging
modalities which can be used to visualize the vortex are MRI and ultrasound. This thesis
presents the work carried out to allow a better characterization of the diastolic vortex in the
left ventricle by Doppler ultrasound imaging. For temporal monitoring of vortex dynamics, a
high temporal resolution is required, since the ventricular diastole is about 0.5 s on average
for a resting human heart. The quality of Doppler signals is also of utmost importance to
get an accurate estimate of the blood flow velocity in the ventricle. To study this vortex, we
focused on evaluating the core vorticity evaluation and especially on its evolution in time.
The work is divided in three parts, and for each of them an article has been written :
1. Ultrafast Doppler sequence : The sequence is based on diverging waves, which resulted
in a high frame rate. In combination with vortography, a method to locate the vortex
core and derive its vorticity, the vortex dynamics could be tracked over time. This
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sequence could establish a proof of concept based on in vitro and in vivo acquisitions
on healthy human volunteers.
2. Triplex sequence : Based on the ultrafast sequence, we were interested in adding information
on the wall motion. The triplex sequence is able to recover not only the
blood motion with a high framerate but also tissue Doppler. In the end, we could
derive color, tissue, and spectral Doppler, along with a high quality Bmode by using
motion compensation. The interdependence between vortex and walls dynamics could
be highlighted by acquiring all the required parameters over a single cardiac cycle.
3. Automatic clutter filter : Vorticity quantification depends directly on the estimation
of Doppler velocity. However, due to their low amplitude, blood signals must be filtered.
Indeed, acquired signals are actually an addition of tissue and blood signals.
Filtering is a critical step for an unbiased and accurate velocity estimation. The last
part of this doctoral thesis has focused on the design of an efficient filter that takes
advantage of the temporal and spatial dimensions of the acquisitions. Thus the tissue
alongside the noise is removed. Particular care was taken to automatize the filter by
applying information criteria based on information theory
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