Persistent Scatterer Interferometric techniques are very powerful geodetic tools for land deformation monitoring that offer the typical advantages of the satellite remote sensing SAR (Synthetic Aperture Radar) systems : a wide coverage at a relatively high resolution. Those techniques are based on the analysis of a set of SAR images acquired over a given area. They overcome the decorrelation problem by identifying elements (in resolution cells) with a high quality returned SAR signal which remains stable in a series of interferograms. These techniques have been useful for the analysis of urban areas, where man-made objects produce good reflections that dominate over the background scattering, as well as in field areas where the density of infrastructures is more limited. Typically, PSI technique requires an approximate a priori temporal model for the detection of the deformation, even though characterizing the temporal evolution of a deformation is commonly one of the objectives of any study.This work is focused on a particular PSI technique, which is named Stable Point Network (SPN) and that it has been completely developed by Altamira Information in 2003. The work concisely outlines the main characteristics of this technique, and describes its main products: average deformation maps, deformation time series of the measured points, and the so-called maps of the residual topographic error, which are used to precisely geocode the PSI products. The main objectives of this PhD are the identification and analysis of the drawbacks of this processing chain, and the development of new tools and methodologies in order to overcome them. First, the performances of the SPN technique are examined and illustrated by means of practical cases (based on real test sites made with data coming from different sensors) and simulated scenarios.Thus, the main drawbacks of the technique are identified and discussed, such as the lack of automatic quality control parameters, the evaluation of the input data quality, the selection of good points for the measurements and the use of a functional model to unwrap the phases based on a linear deformation trend in time. Then, different enhancements are proposed. In particular, the automatic quality control of the coregistration procedure has been introduced through the analysis of the inter-pixel position of some natural point targets-like pixels identified within the images. The enhancements in the selection of the final points of measurements (the final PSI map) come by means of the analysis of the SAR signal signature of the strong targets presented within the image, in order to select only the center of the main lobe as point of measurement. The introduction of robustness within some critical steps of the technique is done by means of the analysis of the rotational of the estimates in close loops within a network of relative measurements, and by means of the implementation of a different integration methodology, which can be ran in parallel in order to compare it with the classical one. Finally, the main drawback of the technique, the use of a linear model for the detection of ground deformations, is addressed with the development of a new fitting methodology which allows possible change of trends within the analyzed time span. All those enhancements are evaluated with the use of real examples of applications and with simulated data. In particular, the new methodology for detecting non-linear ground deformations has been tested in the city of Paris, where a large stacking of ERS1/2 and ENVISAT SAR images are available. Those images are covering a very large time period of analysis at where some known non-linear ground deformations where occurring

Les techniques d'interférométrie sur réflecteurs persistants, ou points stables (PSI), sont des outils particulièrement efficaces pour le suivi des déformations du sol et offrent les avantages typiques des systèmes de télédétection radar à synthèse d'ouverture (RSO) : une large couverture spatiale combinée à une résolution relativement élevée. Ces techniques sont basées sur l'analyse d'un jeu d'images RSO acquises sur une zone donnée. Elles permettent de régler le problème de décorrélation grâce à l'identification d'éléments particuliers (au sein de la cellule de résolution) dont la rétrodiffusion radar est de haute qualité et stable sur toute une série d'interférogrammes. Ces techniques sont fort efficaces (utiles ?) pour l'analyse de zones urbaines où les constructions constituent de bons réflecteurs avec une réflexion supérieure à celle du sol ; il en va de même pour des zones de campagne où la densité d'infrastructures est plus limitée. La technique PSI requiert un modèle temporel approximatif a priori pour la détection des déformations, bien que la caractérisation de l'évolution temporelle de la déformation soit communément l'un des objectifs des études. Le travail réalisé porte sur une technique PSI particulière, appelée Stable Point Network (SPN), Réseau de Points Stables, qui a été totalement développée par Altamira Information en 2003. Le travail présente de manière concise les caractéristiques de la technique et décrit les principaux produits générés : carte moyenne de déformation, séries temporelles de déformation des points mesurés, et les cartes de résidu d'erreur topographique utilisées pour géocoder de façon précise les produits PSI. Le principal objectif de cette thèse est l'identification et l'analyse des points faibles de la chaîne de traitement SPN et le développement de nouveaux outils et méthodologies pour résoudre les problèmes identifiés. Dans un premier temps, les performances de la technique SPN sont examinées et illustrées sur des cas pratiques (basés sur des sites test réels et à partir de données provenant de différents capteurs) et à l'aide de simulations. Les principaux points faibles de la technique sont identifiés et commentés, notamment le manque de paramètres automatiques de contrôle qualité, l'évaluation de la qualité des données d'entrée, la sélection de bons points pour la mesure ainsi que l'utilisation d'un modèle fonctionnel pour le déroulement de phase (franges interferometriques) basé sur une tendance linéaire de la déformation dans le temps. Différentes solutions sont ensuite envisagées. Nous nous intéressons tout particulièrement au contrôle qualité automatique dans la procédure de coregistration, en utilisant l'analyse du positionnement inter-pixel de certains points naturels, comme par exemple des pixels identifiés dans les images. L'amélioration de la sélection finale des points de mesure (carte PSI) s'obtient grâce à l'analyse de la signature du signal radar des cibles les plus puissantes présentes au sein de l'image, afin de sélectionner uniquement le centre du lobe principal du point de mesure. D'autres développements apportent plus de robustesse dans des étapes clefs, ainsi l'analyse du rotationel des estimations en lien étroit avec un réseau de mesures relatives, ou l'implémentation d'une méthodologie différente pour l'intégration qui peut être lancée en parallèle afin d'être comparée avec l'intégration classique. Enfin le principal inconvénient de la technique, c'est-à-dire l'utilisation d'un modèle linéaire de détection des déformations du sol fait l'objet d'un développement d'une nouvelle méthode d'ajustement qui permet des changements de tendance durant la période de temps considérée(...) / Persistent Scatterer Interferometric techniques are very powerful geodetic tools for land deformation monitoring that offer the typical advantages of the satellite remote sensing SAR (Synthetic Aperture Radar) systems : a wide coverage at a relatively high resolution. Those techniques are based on the analysis of a set of SAR images acquired over a given area. They overcome the decorrelation problem by identifying elements (in resolution cells) with a high quality returned SAR signal which remains stable in a series of interferograms. These techniques have been useful for the analysis of urban areas, where man-made objects produce good reflections that dominate over the background scattering, as well as in field areas where the density of infrastructures is more limited. Typically, PSI technique requires an approximate a priori temporal model for the detection of the deformation, even though characterizing the temporal evolution of a deformation is commonly one of the objectives of any study.This work is focused on a particular PSI technique, which is named Stable Point Network (SPN) and that it has been completely developed by Altamira Information in 2003. The work concisely outlines the main characteristics of this technique, and describes its main products: average deformation maps, deformation time series of the measured points, and the so-called maps of the residual topographic error, which are used to precisely geocode the PSI products. The main objectives of this PhD are the identification and analysis of the drawbacks of this processing chain, and the development of new tools and methodologies in order to overcome them. First, the performances of the SPN technique are examined and illustrated by means of practical cases (based on real test sites made with data coming from different sensors) and simulated scenarios.Thus, the main drawbacks of the technique are identified and discussed, such as the lack of automatic quality control parameters, the evaluation of the input data quality, the selection of good points for the measurements and the use of a functional model to unwrap the phases based on a linear deformation trend in time. Then, different enhancements are proposed. In particular, the automatic quality control of the coregistration procedure has been introduced through the analysis of the inter-pixel position of some natural point targets-like pixels identified within the images. The enhancements in the selection of the final points of measurements (the final PSI map) come by means of the analysis of the SAR signal signature of the strong targets presented within the image, in order to select only the center of the main lobe as point of measurement. The introduction of robustness within some critical steps of the technique is done by means of the analysis of the rotational of the estimates in close loops within a network of relative measurements, and by means of the implementation of a different integration methodology, which can be ran in parallel in order to compare it with the classical one. Finally, the main drawback of the technique, the use of a linear model for the detection of ground deformations, is addressed with the development of a new fitting methodology which allows possible change of trends within the analyzed time span. All those enhancements are evaluated with the use of real examples of applications and with simulated data. In particular, the new methodology for detecting non-linear ground deformations has been tested in the city of Paris, where a large stacking of ERS1/2 and ENVISAT SAR images are available. Those images are covering a very large time period of analysis at where some known non-linear ground deformations where occurring

A time-domain backprojection processor for airborne synthetic aperture radar (SAR) has been developed at the University of Massachusetts’ Microwave Remote Sensing Lab (MIRSL). The aim of this work is to produce a SAR processor capable of addressing the motion compensation issues faced by frequency-domain processing algorithms, in order to create well focused SAR imagery suitable for interferometry. The time-domain backprojection algorithm inherently compensates for non-linear platform motion, dependent on the availability of accurate measurements of the motion. The implementation must manage the relatively high computational burden of the backprojection algorithm, which is done using modern graphics processing units (GPUs), programmed with NVIDIA’s CUDA language. An implementation of the Non-Equispaced Fast Fourier Transform (NERFFT) is used to enable efficient and accurate range interpolation as a critical step of the processing. The phase of time- domain processed imagery is dif erent than that of frequency-domain imagery, leading to a potentially different approach to interferometry. This general purpose SAR processor is designed to work with a novel, dual-frequency S- and Ka-band radar system developed at MIRSL as well as the UAVSAR instrument developed by NASA’s Jet Propulsion Laboratory. These instruments represent a wide range of SAR system parameters, ensuring the ability of the processor to work with most any airborne SAR. Results are presented from these two systems, showing good performance of the processor itself.