Synthetic aperture radar (SAR) systems are versatile, high-resolution radar imagers useful for providing detailed intelligence, surveillance, and reconnaissance, especially when atmospheric conditions are non-ideal for optical imagers. However, moving targets in SAR images are smeared. Along-track interferometry is a commonly-used method for extracting the motion parameters of moving targets but requires a dual-aperture SAR system, which may be power- size- or cost-prohibitive. This thesis presents a method of estimating target motion parameters in single-channel SAR data given geometric target motion constraints. I test this method on both simulated and actual SAR data. This estimation method includes an initial estimate, computation of the SAR ambiguity function, and application of the target motion constraints to form a focused image of the moving target. The constraints are imposed by assuming that target motion is restricted to a road. Finally, I measure its performance by investigating the error introduced in the motion estimates using both simulated and actual data.

We propose an exact filtered backprojection algorithm for inversion of the cone beam data in the case when the trajectory is composed of a distorted circle and a line segment. The length of the scan is determined by the region of interest , and it is independent of the size of the object. With few geometric restrictions on the curve, we show that we have an exact reconstruction. Numerical experiments demonstrate good image quality.

A commercial-off-the-shelf Ku-band Frequency Modulated Continuous Wave (FMCW) synthetic aperture radar (SAR) system is coupled with a custom built two-dimensional scanning system. This system is installed in an alpine environment and pointed at a snow-unstable mountain slope for the duration of a Utah winter. The radar scanning system, designed to be capable of mapping a snowpack and its layers, is employed to create a series of three-dimensional images from a remote location. Individual images demonstrate the ability to directly detect snow layers, Furthermore, successive images are compared to track volume magnitude and phase values over the course of winter, including many snow deposition and melt events. The digital signal processing techniques used to create a high-resolution voxel (a three-dimensional pixel) map describing these snow layers is discussed. Results are discussed and further work is suggested for improving upon the results of this work.

No description available.

No description available.

No description available.

No description available.

This dissertation focuses on two different types of responses of Earth; that is, seismic and electromagnetic, and aims to better understand Earth processes at a wider range of scales than those conventional approaches offer. Electromagnetic responses resulting from the subsurface diffusion of applied electromagnetic fields through heterogeneous geoelectrical structures are utilized to characterize the underlying geology. Geology exhibits multiscale hierarchical structure which brought about by almost all geological processes operating across multiple length scales and the relationship between multiscale electrical properties of underlying geology and the observed electromagnetic response has not yet been fully understood. To quantify this relationship, the electromagnetic responses of textured and spatially correlated, stochastic geologic media are herein presented. The modelling results demonstrate that the resulting electromagnetic responses present a power law distribution, rather than a smooth response polluted with random, incoherent noise as commonly assumed; moreover, they are examples of fractional Brownian motion. Furthermore, the results indicate that the fractal behavior of electromagnetic responses is correlated with the degree of the spatial correlation, the contrasts in ground electrical conductivity, and the preferred orientation of small-scale heterogeneity. In addition, these inferences are also supported by the observed electromagnetic responses from a fault zone comprising different lithological units and varying wavelengths of geologic heterogeneity. Seismic signals generated by aftershocks are generally recorded by local aftershock networks consisted of insufficient number of stations which result in strongly spatially-aliased aftershock data. This limits aftershock detections and locations at smaller magnitudes. Following the 23 August 2011 Mineral, Virginia earthquake, to drastically reduce spatial aliasing, a temporary dense array (AIDA) consisting of ~200 stations at 200-400 m spacing was deployed near the epicenter to record the 12 days of the aftershocks. The backprojection imaging method is applied to the entire AIDA dataset to detect and locate aftershocks. The method takes advantage of staking of many seismograms and improves the signal-to-noise ratio for detection. The catalog obtained from the co-deployed, unusually large temporal traditional network of 36 stations enabled a quantitative comparison. The aftershock catalog derived from the dense AIDA array and the backprojection indicates event detection an order of magnitude smaller including events as small as M–1.8. The catalog is complete to magnitude –1.0 while the traditional network catalog was complete to M–0.27 for the same time period. The AIDA backprojection catalog indicate the same major patterns of seismicity in the epicentral region, but additional details are revealed indicating a more complex fault zone and a new shallow cluster. The b-value or the temporal decay constant were not changed by inclusion of the small events; however, they are different for two completeness periods and are different at shallow depth than greater depth. / Ph. D.

Une des thématiques abordée par l'équipe Image et Vidéo-Communication est la reconstruction tomographique discréte à l'aide de la transformée Mojette. Ma thèse s'inscrit dans le cadre de la reconstruction tomographique médicale. La transformée Mojette est une version discrète exacte de la transformée de Radon qui est l'outil mathématique permettant la reconstruction tomographique. Pour évaluer la qualité des reconstructions, nous avons utilisé des fantômes numériques 2D simples (objet carré, rond) en absence puis en présence de bruit. Le coeur de mon travail de thèse est la reconstruction d'un objet à l'aide d'un algorithme de rétroprojection filtrée exacte Mojette en absence de bruit s'appuyant sur la géométrie discrète. Pour un nombre fini de projections dépendant de la taille de l'objet à reconstruire la reconstruction est exacte. La majorité des tomographes industriels utilisent l'algorithme de rétroprojection de projections filtrées (Filtered Back Projection ou FBP) pour reconstruire la région d'intérêt. Cet algorithme possède deux défauts théoriques, un au niveau du filtre utilisé, l'autre au niveau de la rétroprojection elle-même. Nous avons pu mettre au point un algorithme de Mojette FBP. Cet algorithme fait partie des méthodes directes de reconstruction. Il a aussi été testé avec succès en présence de bruit. Cet algorithme permet une équivalence continu-discret lors de la reconstruction. L'étape de projection/rétroprojection Mojette présente la particularité intéressante de pouvoir être décrit par une matrice Toeplitz bloc Toeplitz. Pour utiliser cette propriété nous avons mis en oeuvre un algorithme de gradient conjugué.

Le cadre de cette thèse est centré sur l'étude d'un radar ultra large bande (ULB) en mode impulsionnel, pour la « vision » à travers les murs (VAM), qui présente de nombreuses applications tant dans le domaine militaire (lors des assauts, des prises d’otages, …) que dans le secteur de la sécurité civile (recherche de personnes dans des décombres, dans un incendie, ...). Pour ces utilisations, l’image réelle de la scène observée n’est pas nécessaire, seules certaines informations pertinentes suffisent : nombre de personnes, position, vitesse de déplacement, etc. C'est dans ce contexte que nous avons développé un dispositif expérimental de détection et des techniques de localisation de cibles derrière un mur. Le radar développé est constitué d’un émetteur impulsionnel couvrant la gamme de fréquence de 3 GHz à 6 GHz, et de trois récepteurs indépendants, associés à des algorithmes de localisation et de reconstruction d'image.Le premier algorithme repose sur une technique de trilatération. Une fois, le modèle théorique présenté, plusieurs méthodes de résolution sont étudiées pour l'estimation de la mesure de la distance de propagation du signal. La méthode de Brent-Dekker a été retenue pour sa rapidité de convergence et son faible nombre d’itérations. Bien que cette technique soit précise, elle ne permet pas d’obtenir une image de la scène, mais juste de localiser les cibles, sans apporter des informations sur ses dimensions. C’est pourquoi une seconde approche, basée sur une « formation de faisceau », a été étudiée, afin d'obtenir une représentation 2D de la scène. Nous avons choisi de développer une méthode de rétroprojection non cohérente, technique la plus simple qui ne nécessite pas de contrainte forte sur la phase du signal ni sur le positionnement des antennes. Différentes variantes de rétroprojection ont été proposées : la rétroprojection avec cross corrélation, la rétroprojection cross corrélation améliorée et la rétroprojection bicross corrélée. Ces trois méthodes reposent sur une fusion d'informations capturées par l'antenne réceptrice avec celles obtenues sur des antennes dites de référence. Cette fusion a permis d'améliorer progressivement le rendu des images.Pour conclure ses travaux, une perspective est ébauchée afin de minimiser le taux de fausse détection, elle s'appuie sur la collaboration de la technique de trilatération avec la technique de rétroprojection bicross corrélée. Cette collaboration permet de mettre en correspondance les détections estimées par la technique de trilatération et celles utilisant la rétroprojection bicross corrélée. Les cibles non appariées sont alors supprimées selon des critères spécifiques à chacune des deux approches. / The content of this thesis is focused on the study of an UWB pulse radar for through the wall vision which has many applications in the military domain (assaults, hostage rescue,…) and in the civil security domain (people search in the rubble, in a fire).For these uses, the real observed scene image is not necessary, only some relevant information is enough: number of persons, position, velocity of movement, etc. It’s in this context where we have developed an experimental detection device and some through the wall targets localization techniques. The developed radar consists of a pulse transmitter covering the frequency range from 3GHz to 6GHz, and three independent receivers, combined with some localization algorithms and image reconstruction.The first algorithm is based on a technique of trilateration. Once the theoretical model is presented, many resolutions methods are studied for estimation of the signal propagation distance measurement. The Brent-Dekker method has been chosen for its fast convergence and low number of iterations. Although the trilateration technique is accurate, it does not allow obtaining a scene image, but just locate the targets, without providing their dimensions. Therefore a second approach, based on a “beam forming”, has been studied, in order to obtain a 2D scene representation. We have chosen to develop a non-coherent backprojection method, it is the most simple technique which does not require a strong constraint on the signal phase nor on the antenna positions. Different backprojection methods have been proposed: the backprojection with cross correlation, the improved backprojection with cross correlation and bi-cross correlated backprojection. These three methods are based on a fusion of captured information by the receiving antennas and with the obtained information on the “referenced” antennas. This fusion allows improving the image quality progressively.To conclude this work, a perspective is initiated in order to minimize the false detection rate, it is based on the cooperation of the trilateration technique and bi-cross correlated backprojection. This cooperation allows matching the estimated detection by the trilateration technique and the bi-cross correlated backprojection technique. The mismatched targets are removed according to some specific criterias to each approach.