Dissertations / Theses on the topic 'SAR'

O trabalho realizado teve como objetivo implementar um processo de autofocalização baseado no "Mapdrift" em um processador SAR que utiliza o algoritmo "Range Doppler"para gerar imagens a partir do sensor SAR aeroembarcado do SIVAM. O processo implementado utiliza a seleção de linhas azimutais de um bloco de dados brutos do Radar baseado na largura e pico da correlação entre dois "looks" para estimar o parâmetro de autofocalização do filtro azimutal. Os resultados mostram que o processamento de imagens que utiliza a seleção de linhas azimutais é mais rápido e gera qualidade focal semelhante se comparado com o processo que utiliza todas as linhas azimutais de um bloco de dados. Notou-se que a qualidade da focalização é melhorada quando se reduz o tamanho das linhas azimutais, mas o tempo de processamento é aumentado. Também se verificou a utilização de um conjunto dos dados coletados nas quatro polarizações (Lhh, Lvv, Lvh e Lhv) para estimar o parâmetro de focalização gera imagem de qualidade semelhante ao processo que utiliza apenas uma banda (Lhh).

Las técnicas de Interferometría Diferencial se basan en la combinación de varias imágenes SAR con distinta separación temporal y permiten la recuperación de las componentes lineales y no-lineales del proceso de deformación ocurrida en el entorno de interés durante el entero periodo de observación. Condición imprescindible para una correcta estimación de los fenómenos geodéticos es la elevada estabilidad de la plataforma que embarca el sensor SAR. Por esta razón, a nivel operativo se utilizan datos SAR satelitales.
El objetivo de la Polarimetría SAR es describir el entorno de interés analizando las propiedades de la señal que éste dispersa cuando se utilizan diferentes combinaciones de polarización de las antenas transmisora y receptora, definidas canales polarimétricos. La polarimetría interferométrica SAR junta la capacidad de la polarimetría de separar mecanismos de dispersión independientes con la sensibilidad de la Interferometría a la altura de los correspondientes centros de fase, y permite describir la distribución volumétrica de los dispersores dentro de la escena observada. Debido a la falta de conjuntos de datos polarimétricos SAR satelitales que cubran tramos temporales suficientemente largos, hay aún un gran interés en las mejoras que la polarimetría podría aportar a técnicas ya consolidadas como las de Interferometría Diferencial.
La actividad de investigación que se presentará en esta tesis doctoral abarca, por primera vez conjuntamente, las dos áreas de la Polarimetría SAR y de la Interferometría Diferencial utilizando el sensor radar terrestre de corto alcance (gbSAR) desarrollado por la Universitat Politècnica de Catalunyua (UPC). El trabajo constará de dos bloques principales.
El primer bloque describirá las técnicas que se han desarrollado para convertir el sistema UPC gbSAR en un instrumento operativo y simplificar la utilización de sus adquisiciones, incluyendo la formulación matemática de los principios de funcionamiento del sistema, la cadena de procesado de los raw data y su calibración polarimétrica, los procedimientos de georeferenciación, y las técnicas de compensación de los artefactos atmosféricos presentes en sus medidas diferenciales.
La segunda parte se ocupará de demostrar los beneficios que los datos SAR polarimétricos ofrecen respecto a la medición de un único canal polarimétrico para aplicaciones diferenciales. A fin de llevar a cabo esta tarea, se analizarán los datos gbSAR adquiridos durante una campaña de medidas de un año realizada en el pueblo de Sallent, en Cataluña, afectado por un fenómeno de subsidencia. En esta parte se analizarán tres temas principales. El primero es el comportamiento no estacionario en tiempo del entorno urbano bajo la geometría de observación del sensor terrestre. Se estudiarán en detalle los efectos de su inestabilidad y se propondrá una técnica de filtrado novedosa entallada a las propiedades de los blancos deterministas con el fin de preservar la información de la fase diferencial. El segundo tema abarca el problema de los efectos de troposfera en datos diferenciales con separación temporal superior al mes y de su separación de las variaciones de fase inducidas por el proceso de deformación. El tercer tema es la utilización de toda la información polarimétrica diferencial. Con fin de superar las limitaciones propias de las técnicas DInSAR clásicas, se propondrá un nuevo modelo polarimétrico de dispersión y se demostrarán las ventajas de la nueva formulación enseñando la mejor estimación del proceso de subsidencia en Sallent. En la parte final de este apartado se explorará también el potencial de las técnicas polarimétricas de optimización de la coherencia para aplicaciones diferenciales.
Differential SAR interferometry (DInSAR) deals with the combination of multi-temporal SAR images for the estimation of the linear and non-linear components of the deformation process within an area of interest during the whole observation period. A high stability of the platform is required for a reliable estimation of the geodetic phenomena. Accordingly, space-borne SAR images are operatively employed for DInSAR estimation, air-borne DInSAR still constituting a challenging research issue. SAR
Polarimetry aims at charactering the illuminated area through the analysis of its response under different combinations of transmitting and receiving antennas polarization, called polarimetric channels. The Polarimetric SAR Interferometry joins the capability of Polarimetry to separate independent scattering mechanisms and the sensitivity of Interferometry to the corresponding phase centers' elevation, making it possible to describe the volumetric distribution of the scatterers within the observed area. Owing to the lack of long-time collections of polarimetric space-borne SAR data, the studies carried out in this research field have been mainly based on air-borne acquisitions. Yet, there is a great expectation for the improvements that polarimetry may bring to assessed single-polarization techniques such as the DinSAR.
The research described in this PhD dissertation fills for the first time the gap between SAR Polarimetry and SAR Differential Interferometry through the employment of an X-band ground-based SAR (gbSAR) sensor developed by the Remote Sensing Lab of the Universitat Politècnica de Catalunya (UPC).
The work is divided into two main blocks. The first part deals with the algorithms that have been developed to make the UPC system operative and its acquisitions easy to use. Summarily, they include the mathematical formulation of the sensor's working principles, the raw data processing chain and the polarimetric calibration method, the geocoding procedures, and the techniques compensating for the atmospheric artefacts affecting gbSAR zero-baseline acquisitions.
The second part is concerned with demonstrating the benefits that polarimetric SAR measurements provide with respect to single-polarization data for differential applications. In order to cope with this task, the data sets acquired during a one-year measurement campaign carried out in the village of Sallent, northeastern Spain, are analyzed. The experiment was focused on monitoring the subsidence phenomenon affecting a district of the village with the UPC gbSAR sensor. Three main issues are here argued. The first one is the time non-stationary behaviors characterizing the urban environment at X-band in the gbSAR observation geometry. Their effects are analyzed in detail and a novel non-stationary filtering technique tailored to deterministic scatterers' properties is introduced to preserve the differential phase information. The second one is the compensation of the troposphere changes in long-time span gbSAR differential interferograms. A new technique is worked out to effectively separate the differential phase variations due to the atmospheric artefacts from the deformation components. The third one is the use of the whole polarimetric differential information. A novel polarimetric differential scattering model is put forward to relax the constraints of an advanced DInSAR technique, the Coherent Pixel Technique, and to propose an innovative polarimetric approach. The advantages offered by Polarimetric DInSAR are demonstrated in terms of quality of the deformation-rate map describing the subsidence phenomenon in Sallent. In the end, the potentials of coherence-optimization techniques for the further improvement of the deformation process estimation are stressed.

Includes bibliography.
This dissertation deals with a comprehensive literature review on SAR polarimetric calibration, as well as developing a polarimetric calibration procedure to be used for calibrating the sensor for the Waseda SAR project. The complete work is presented in six chapters. The dissertation starts by introducing Synthetic Aperture Radar Polarimetry (SAR polarimetry) by identifying the research objectives, and explains Waseda SAR project between King Abdulaziz City for Science and Technology and the University of Cape Town. A comprehensive literature review on SAR polarimetric calibration is introduced in the dissertation. The literature review explains the developments in calibration methods from the early 1960’s to recent years, including passive and active reflector advantages as well as the limitations for both reflectors. Also, displaying the received power as a function of polarization in a graphic way is presented in the dissertation known as the ‘polarization signature’. Two examples are used which are: the trihedral corner reflector and the dihedral corner reflector. The two examples are the theoretical reference for the calibration procedure for Waseda SAR sensor. The calibrated data set collected from NASA’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) over California is analyzed. The data is contaminated with an unrealistically high amount of coupling (-5 dB) to show the coupling effect on the data and then remove the amount of coupling to return the data to its original form. The dissertation concludes with a calibration procedure to be used for calibrating Waseda SAR sensor using the presented methods of SAR polarimetric calibration. The procedure involves using external devices such as: trihedral corner reflectors and dihedral corner reflectors as well as calculating the sizes of the reflectors and how the calibration flights are to be coordinated and instrumented with the reflectors.

Bibliography: pages 120-121.
This thesis explores various methods of using PVM (Parallel Virtual Machine) to improve the speed of processing a SAR (Synthetic Aperture Radar) image. A network of heterogeneous machines were set up as the basis of the parallel virtual machine. SAR processing software was written for testing the PVM. The software performed simplified range and azimuth compression on simulated SAR images of a point target The theory and results were examined as part of the thesis. Complications such as range curvature, range migration and range dependent focusing were not addressed.

The sigma (σ) receptor is a neuromodulatory protein, widely expressed in the central nervous system (CNS) and to a lesser extent, the peripheral nervous system (PNS). Currently, two sigma receptor subtypes are known; sigma-1 receptors (S1R) and sigma-2-receptors (S2R), differing in molecular weight, pharmacological profile, distribution and function. The S1R has been implicated in depression, schizophrenia, Alzheimer’s disease, Parkinson’s disease, drug abuse and more recently for its involvement in analgesia. The design of highly subtype-selective ligands is limited by a lack of information regarding the S1R/S2R binding site, a lack of crystal structure data on S1R until 2016, as well as a large structurally-diverse collection of known ligands. The currently accepted pharmacophore arising from this extensive ligand library proposes an alkylamine core tethered by two hydrophobic groups. Several highly subtype-selective S1R ligands fitting this pharmacophore have been previously synthesised in the Kassiou laboratory. This project investigates the optimisation of the lead 1-(benzofuran-2-ylmethyl)-4-(4-methoxybenzyl)piperazine with considerable focus on the flexibility and basicity of the piperazine core. Furthermore, bioisosteres of piperazine, phenyl, and the size tolerance of the hydrophobic sites of the S1R are also investigated. Binding affinities and sub-type selectivities were determined by in vitro binding assays of both S1R and S2R, with structure-activity relationships drawn from these modifications. This work aims at refining the S1R pharmacophore and to create S1R-selective ligands that can be used as probes to further understand the physiological role, as well as the morphology, of the S1R receptor. Ultimately, they may lead to remedies to treat the CNS diseases associated with this receptor.

Els oceans mantenen una fràgil i complexa cadena que enllaça un alt nombre de factors biològics, sociològics i econòmics. Actualment, aquest ecosistema està amenaçat per l'activitat humana i uns dels punts més crítics és la sobreexplotació pesquera. Això ha despertat la consciencia de les autoritats d'arreu per a protegir l'entorn marí i assegurar, així, la seguretat i supervivència dels éssers humans. Tal objectiu demana el desenvolupament de polítiques de control que monitorin l'activitat dels vaixells.

Fins l'actualitat, diferents propostes s'han estudiat per monitorar vaixells, com per exemple transpondedors, teledetecció òptica i sensors acústics passius. L'experiència en entorns reals ha demostrat que cap d'aquestes solucions és eficient. Una alternativa poden ser els Radars d'Obertura Sintètica (SAR). Aquests sistemes utilitzen les propietats de reflectivitat i dispersió dels vaixells per identificar-los amb independència de qualsevol fenomen atmosfèric i del cicle dia/nit. El sensors SAR sintetitzen una obertura més gran que la real permetent l'obtenció d'imatges de reflectivitat d'uns quants kilòmetres d'amplada amb una resolució de pocs metres.

En la monitorització de vaixells, la tecnologia SAR ha demostrat unes bones prestacions per la detecció. Treu profit del fet que els vaixells dispersen més energia que el mar i, així, apareixen en les imatges com punts molt brillants. Però, la seva utilitat en la identificació de vaixells encara no està clara. Hi ha dues limitacions importants: 1) les resolucions dels sistemes actuals no semblen suficients per aïllar característiques geomètriques a partir de la informació de reflectivitat i 2) les distorsions que les signatures dels vaixells experimenten en entorns marins. Aquests problemes es poden resoldre parcialment si s'utilitzen dades SAR multidimensional. Aquest concepte es refereix al fet d'adquirir imatges SAR modificant un o més paràmetres del sistema. En la classificació de vaixells, hi ha dues opcions clares: 1) Polarimetria SAR (PolSAR) que utilitza les dues components polarimètriques de l'ona EM i 2) la Interferometria SAR que s'obté per la combinació de dues imatges SAR adquirides des de posicions molt properes. Per a una banda, la polarització de l'ona EM és una propietat intrínseca de l'ona que ajuda a aïllar estructures geomètriques particulars per mitjà de la teoria de descomposició de blancs (TD). Per l'altra, la interferometria treu profit de la diferencia de fase entre les dues imatges SAR per obtenir la tercera dimensió de l'escena.

PolSAR and InSAR presenten grans possibilitats per la monitorització de vaixells ja que poden solucionar algunes de les limitacions dels mètodes clàssics. Desafortunadament, encara no han estat profundament estudiades a causa de les dificultats en obtenir dades reals validades. Això ha limitat el nombre d'estudis en aquesta temàtica. En aquest entorn, la tesi està orientada a avaluar fins a quin punt les tècniques PolSAR i InSAR poden ser útils per la monitorització de vaixells. Per a tal propòsit, s'han fixat quatre objectius importants:
1. El desenvolupament d'un simulador SAR eficient que doni imatges realistes de vaixells i que solucioni el dèficit de dades reals en entorns marins.
2. L'estudi de la dispersió dels vaixells que fixi els principals mecanismes de dispersió observats en imatges SAR i com es relacionen amb la geometria dels vaixells.
3. Un estudi de les prestacions de les tècniques actuals d'anàlisis de dades PolSAR en la classificació de vaixells.
4. El desenvolupament d'un mètode nou i eficient per la identificació de vaixells.

Al llarg de la tesis, els diferents punts seran estudiats i resolts. El desenvolupament de GRECOSAR, un simulador SAR de blancs complexes que dóna imatges de vaixells similars a les adquirides en entorns reals, ha estat essencial per estudiar les propietats de dispersió dels vaixells. Ha permès demostrar que els vaixells es poden distingir a partir del seu patró dispersiu, el qual és senzill i dominat per alguns dispersors guia que presenten una marcada estabilitat i potència de dispersió. Amb aquests resultats ha estat possible desenvolupar un nou mètode que pot identificar vaixells sota condicions d'observació adverses. Combina característiques polarimètriques i interferomètriques SAR (PolInSAR) per inferir estimacions 3D de la geometria dels vaixells. Diferents tests han demostrat que aquest mètode dóna una millor fiabilitat en la identificació que altres mètodes actualment disponibles. Malgrat tot, fixa uns requeriments tecnològics més elevats, sobretot en la resolució de les imatges i en les característiques PolInSAR. La nova generació de sensors SAR els poden cobrir.
Oceans support a complex and fragile chain that links a high number of biological, sociological and economical factors. In these days, this ecosystem is endangered by human activity and one of the main hot spots is overfishing. As a result, authorities worldwide have become aware about the necessity to law-protect the marine environment in order to assure the safety and sustenance of human beings. This demands the development of fisheries policy to monitor the activities of ships.

Up to now, different vessel monitoring proposals have been considered, for instance transponders, optical remote sensing or passive acoustic sensors. The lessons learnt in real scenarios have shown that none of these solutions is efficient. A feasible option may be the so-called active Synthetic Aperture Radar (SAR) technology. It uses the reflectivity/scattering properties of vessels for basing the identification process with independence of any atmospheric phenomena and day/night cycle. SAR sensors synthesize an antenna aperture larger than the real one and this allows to acquire reflectivity images of some tens of kilometers wide with a resolution of few meters.

In vessel monitoring, SAR imagery has proven good performance for vessel detection. They take profit of the fact that vessels normally backscatter more power than the sea and, hence, they appear in the images as bright spots. But their usefulness in vessel identification has not been established yet. There are two main limitations, namely: 1) the resolution of current systems that appears to be not enough for isolating geometrical features from the reflectivity information of SAR images and 2) the distortions that vessel' signatures experiment within sea scenarios. Such problems can be solved up to certain extend if multidimensional SAR data is used. This concept refers to the possibility to acquire different SAR images by modifying one or more imaging parameters. In the scope of vessel classification, there are two main options, namely: 1) SAR polarimetry (PolSAR) that refers to the usage of the two polarimetric components of the EM wave and 2) SAR interferometry (InSAR) derived by combining two SAR images acquired from slightly different positions. On the one hand, the polarization of an EM wave is an intrinsic wave property that helps on identifying specific geometrical structures via Target Decomposition (TD) theory. On the other hand, Interferometry takes profit of the phase difference between the two SAR images to retrieve the third dimension of the scene.

PolSAR and InSAR have great potentialities for supporting vessel monitoring as they can overcome some of the limitations of classical methods. Unfortunately, they have not been exploited yet due to the difficulties on having at one's disposal real data with reliable ground-truth. This has limited the number of works tackling such issue. In this framework, the current thesis is focused to evaluate up to which extend PolSAR and InSAR imagery are reliable for vessel monitoring. For such purpose, four main goals are proposed, namely:
1. The development of an efficient SAR simulation environment that provides realistic vessel SAR images and overcomes the current data deficiency related to marine scenarios.
2. The study of vessel scattering to fix the main polarimetric scattering mechanisms observed in vessel SAR images and how they are related with the geometries of vessels.
3. A performance study of current analysis tools of PolSAR data in vessel classification.
4. The development of a novel and efficient methodology for vessel identification.

Along the thesis, the different points are studied and solved. The development of GRECOSAR, a SAR simulator of complex targets able to provide vessel images similar to those obtained in real scenarios, has been essential for studying the scattering properties of vessels. It has allowed to show that vessels can be distinguished by means of their scattering pattern, which appear to be not so complex and dominated by some guide scatters that present a marked reflectivity stability and scattered power. With these results, a new approach able to identify vessels even under adverse observation conditions has been developed. It combines polarimetric and interferometric SAR (PolInSAR) capabilities to retrieve 3D estimates of the geometry of ships. Different tests have shown that the proposed method provides better identification confidence than other available methods. However, it demands higher technological requirements in terms of image resolution and PolInSAR features. The new generation of SAR sensors may fulfill them.

L'obtention d’images à partir de l'émission, de la réception et du traitement d'impulsions radar (SAR) est soumise à différentes contraintes qui limitent les performances telles que la résolution en distance, la résolution en azimut ou la largeur de la Zone imagée (fauchée). Ces limites sont en partie liées à la dimension finie de l’antenne, en particulier dans le cas du SAR spatial. Pour cette raison, on a cherché à étudier la possibilité de mettre au point des systèmes SAR spatiaux distribués, c'est-à-dire dont la surface d'antenne globale est répartie sur plusieurs plates-formes (généralement microsatellites pour des raisons de coût). Ce concept a déjà été instruit dans des concepts de formations comme la Roue lnterferométrique, le Pendulum ou TechSat21. Dans le cadre de mes travaux, deux configurations seront présentées. La première repose sur N antennes réparties successivement sur une même orbite («Train SAR»). On montre que, moyennant des contraintes de positionnement fortes, une telle formation permet, à surface globale d'antenne égale, d’augmenter d’un facteur N le rapport fauchée sur résolution azimut par rapport à une antenne monolithique. Cependant, les simulations effectuées montrent que le positionnement strict nécessaire pose un problème, dont une solution étudiée est l'utilisation de formes d’ondes à spectre étalé. Par ailleurs, le passage d’une antenne monolithique sur un satellite de grande taille à un ensemble de petites antennes sur des microsatellites, a fait l’objet d’une étude de dimensionnement. La deuxième formation repose sur deux satellites fonctionnant à la même fréquence, ayant la même bande émise, placés de telle manière qu’ils observent la même fauchée à deux incidences proches. Cette situation peut être ramenée à une observation à la même incidence, avec deux bandes émises décalées. On peut alors obtenir une bande émise virtuelle plus large, donc une résolution distance plus fine. Après avoir appliqué l'algorithme à des signaux simulés, il a été utilisé sur des images réelles ENVISAT. Les résultats seront présentés, ainsi qu’une première étude de dimensionnement. Enfin, on conclura sur les pistes d’études futures mises en évidence par ces travaux, et sur l’apport possible des systèmes distribués dans le cadre du SAR spatial.

During the last decades Radar altimetry became an important tool to observe the sea surface with respect to sea level and sea state. Since the launch of CryoSat-2 a new technique called SAR altimetry improves the signal to noise ration of retrieved geophysical parameters and due to the smaller along track footprint a better performance in coastal zones is reached. In the last years several new processing modes were developed and tested to improve the understanding of this new technique such as reduced SAR (RDSAR), low resolution mode including range cell migration correction (LRMC) and fully focused SAR processing. The scope of this work is to improve the retrieval of geophysical parameters by developing a new stack and waveform model capable of including more general sea surface representations such as the geoid and introducing vertical wave particle motions. This new model will be included in different retracking schemes to investigate how the retrieved geophysical parameters change with respect to accuracy and precision. It is shown that 20 Hz SAR processing, which is used in the official level two data products, results in an aliasing of the sea surface and that a surface sampling rate of 40 Hz will yield a lower pink noise floor and more precise retrieved parameters whereas the other two considered processing modes RDSAR and LRMC do not benefit from a higher sampling rate. Another contribution of this work is the investigation of possible effects of sea surface slopes and curvatures on RDSAR, LRMC and unfocused SAR processing. It can be concluded that the impact of these quantities is small in RDSAR and SAR processing whereas in LRMC processing significant wave height biases up to three metre and sea level biases between minus twenty and plus twenty centimetres can occur if the surface slopes and curvatures are not considered correctly in the signal processing and parameter retrieval process. On the other hand LRMC is capable of estimating geophysical parameters consistent to the other two considered processing modes with a better precision as unfocused SAR. In the last part it will be shown that the standard deviation of vertical wave particle velocities is an estimable parameter with a high correlation with respect to model and in-situ data. Additionally considering this geophysical parameter in the retracking can lead to consistent wave height estimations with RDSAR at high sea states which was an open issue as mean differences up to twenty centimetres occurred between these two processing modes. However, at small sea states the accuracy is not good due to differences in significant wave height up to one metre and sea level differences up to seven centimetres. This means that there is still a need for further improvements within zero to two metres significant wave heights which needs to be addressed in further studies.

Synthetic Aperture Radar (SAR) is a popular tool for airborne and space-borne remote sensing. Inherent to SAR imagery is a type of multiplicative noise known as speckle. There are a number of different approaches which may be taken in order to reduce the amount of speckle noise in SAR imagery. One of the approaches is termed post image formation processing and this is the main concern of this thesis. Background theory relevant to the speckle reduction problem is presented. The physical processes which lead to the formation of speckle are investigated in order to understand the nature of speckle noise. Various statistical properties of speckle noise in different types of SAR images are presented. These include Probability Distribution Functions as well as means and standard deviations. Speckle is considered as a multiplicative noise and a general model is discussed. The last section of this chapter deals with the various approaches to speckle reduction. Chapter three contains a review of the literature pertaining to speckle reduction. Multiple look methods are covered briefly and then the various classes of post image formation processing are reviewed. A number of non-adaptive, adaptive and segmentation-based techniques are reviewed. Other classes of technique which are reviewed include Morphological filtering, Homomorphic processing and Transform domain methods. From this review, insights can be gained as to the advantages and disadvantages of various methods. A number of filtering algorithms which are either promising, or are representative of a class of techniques, are chosen for implementation and analysis.

Remote sensing and surveillance are the main application areas for radar in general and synthetic aperture (SAR) radar in particular. Since the first radar system built by Hülsmeyer in 1904, radar has developed so that it is now able to create images from a large distance. In addition to this, the invention of synthetic aperture radar has enabled the ability to create images with high resolution. In this thesis, SAR systems capable of very high resolution imaging are considered, and data from such a system, namely CARABAS-II, is used. The higher the resolution of the system, the better the ability to extract information. The work presented in this thesis can be divided into two separate fields. The first and main area is speed estimation and the refocusing of moving targets in SAR imagery. The second area is related to SAR processing. In Part I of this thesis, a theoretical expression for the phase of a moving object in a SAR image is derived. Based on this expression, an estimator of relative speed is proposed. The estimator was tested in simulation and on CARABAS-II data, using a boat as a moving target. The results with regard to the focusing ability were satisfactory. In Part II, a comparison between two high resolution SAR processing algorithms, namely the polar and the subimage version of fast factorized back projection, is made. The comparison takes into account the difference in ability of obtaining very high quality images and gives a phase error analysis. In Part III, the effect of clutter statistics on the estimator is investigated. The sensitivity of the estimator to surrounding stationary targets (coherent clutter) and to thermal noise is examined. The results indicate that a target signal power of approximately 5dB above clutter (peak energy) or noise (average power) gives good results only using one iteration. Part IV is a continuation of Part I and III. In this part, a refocusing approach based on a SAR image is also developed and used. The central part of this refocusing approach is the derivation of a new refocusing equation. The results show that an image with many moving targets that have different normalized relative speeds can be focused.

Le tecniche Multi-temporali SAR interferometriche (Mt-InSAR) rappresentano oggigiorno strumenti consolidati per mappare l’evoluzione temporale dei fenomeni di deformazione del suolo Terrestre. Queste tecniche utilizzano congiuntamente sets di interferogrammi SAR differenziali al fine di estrarre la componente legata alla deformazione e produrre così serie storiche di deformazione dei bersagli osservati dal sensore. L'affidabilità delle misure prodotte utilizzando algoritmi Mt-InSAR è strettamente legata alla capacità degli stessi algoritmi nell’isolare esclusivamente i segnali legati alla deformazione dal segnale complessivo interferometrico, e questa operazione diventa sempre più complessa all’aumentare dei livelli di rumore in ciascun interferogramma SAR coinvolto. Le tecniche Mt-InSAR canoniche sono altamente affidabili nel monitorare l'evoluzione dello spostamento dei target che risultano essere ampiamente stabili o coerenti per tutto il periodo di analisi. Diversamente, quando i bersagli sono particolarmente affetti da problemi di decorrelazione, le stime di deformazione ottenute risultano corrotte e inaffidabili. Questo pone le basi per lo sviluppo di processori Mt-InSAR avanzati che possano fornire stime accurate della deformazione del suolo anche in scenari con problemi di decorrelazione più o meno severi. In questo lavoro di tesi affronta dapprima lo studio dello stato dell’arte delle tecniche Mt-InSAR canoniche applicabili sia nel caso di piattaforme satellitare che terrestri, e dopodiché si propongono delle nuove tecniche Mt-InSAR per superare alcune delle criticità riscontrante. In particolare si studiano le tecniche convenzionali Mt-InSAR multigriglia per l'analisi dei target alla griglia di risoluzione spaziale più risoluta, evidenziandone le loro criticità in aree a media e bassa coerenza, e proprio in questo ambito è proposta una tecnica innovativa per meglio operare in ambienti decorrelati. Il metodo proposto si basa su efficienti operazioni con cui viene srotolata la fase (PhU) interferometrica eseguite alle scale spaziali native, ed in particolare, si srotolano dapprima gli interferogrammi alla scala di soluzione mediata (ML) attraverso algoritmi di PhU convenzionali (o avanzati). Successivamente, gli interferogrammi ML srotolati vengono utilizzati per facilitare le operazioni di PhU eseguite alla scala più fine (single-look). In dettaglio, gli interferogrammi multi-look srotolati vengono ricampionati alla griglia single-look e sottratti a modulo modulo-2π agli interferogrammi single-look. Gli interferogrammi epurati dai contributi a bassa frequenza vengono poi srotolati e aggiunti nuovamente agli interferogrammi multilook ricampionati alla griglia di risoluzione più fine. Per realizzare queste operazioni, a differenza dei metodi multigriglia canonici, non si utilizza alcun modello (lineare/non lineare) per recuperare le componenti di deformazione in alta frequenza. Infine, gli interferogrammi single-look srotolati sono opportunamente invertiti al fine di calcolare le serie storiche di deformazione del suolo attraverso un qualsiasi algoritmo a piccola baseline (SB) InSAR multi-temporale. I risultati sperimentali sono stati ottenuti elaborando una serie di dati SAR acquisiti dal sensore COSMO-SkyMed (banda X) sulla zona costiera di Shanghai, in Cina. La tesi prosegue analizzando le tecniche ai minimi quadrati pesate (WLS) e su come sono sfruttate nell’ambito InSAR al fine di migliorare l’operazione con cui si srotola la fase interferometrica e la generazione di serie storiche di deformazione. Proprio in questo contesto, utilizzando gli approcci WLS, si estende l'utilizzabilità dell'algoritmo Mt-InSAR Small BAseline Subset (SBAS) in aree caratterizzate da una coerenza spaziale medio-bassa. In particolare, pixel per pixel, si invertono esclusivamente le fasi interferometriche coerenti utilizzando una metrica a minimi quadrati pesati. Per cui attraverso una selezione adattiva, per ogni pixel si utilizzano ed invertono soltanto le fasi interferometriche coerenti, e tale caratterista può portare a diversi sottoinsiemi disgiunti di dati SAR, che sono poi invertiti sfruttando la Decomposizione a Valori Singolari Pesata (WSVD). Tuttavia, per taluni pixel, l’utilizzo esclusivo delle fasi interferometriche coerenti può portare in alcuni casi allo scarto di acquisizioni SAR particolarmente rumorose, il che si traduce in serie storiche di deformazione affidabili ma con campionamento temporale variabile. I risultati sperimentali sono stati condotti applicando la tecnica sviluppata ad un set di dati SAR acquisiti dai sensori COSMO-SkyMed (CSK) sulla regione Basilicata, nel sud Italia. Il lavoro di tesi continua analizzando le proprietà che ledono alla irrotazionalità delle triplette di fase di interferogrammi SAR multi-look. In particolare, si studiano le conseguenze delle incongruenze temporali di fase dei multi-look sulla generazione delle serie storiche di deformazione del suolo attraverso metodi SB Mt-InSAR. La ricerca condotta mostra come queste incongruenze di fase si possono propagare attraverso una rete temporale ridondante di interferogrammi SB, ed insieme agli errori di PhU, pregiudicano la qualità dei prodotti InSAR generati. In letteratura questo effetto va sotto il nome di bias di fase, il quale può pregiudicare l’affidabilità dei metodi SB quando si impostano delle soglie sulla massima baseline temporale troppo stringenti (nell’ordine di 30 giorni o meno). Proponiamo così, due nuovi metodi per la compensazione di tali fenomeni di bias, i quali metodi sono stati testati utilizzando dati SAR simulati e reali. I dati reali sono stati acquisiti dai sensori Sentinel-1A/B (banda C) sulle aree del Nevada (U.S.), e sulla zona del monte Etna in Sicilia, nel sud Italia. Dopo lo sviluppo di algoritmi per la parte satellitare, il lavoro si sposta sui sensori SAR terrestri (GB-SAR). In questo ambito proponiamo un metodo per stimare e compensare i disturbi introdotti dallo strato atmosferico (APS) in interferogrammi GB-SAR. Un’ambia analisi fisica, statistica e matematica dell'approccio presentato è fornita, discutendo inoltre le potenzialità e i limiti del metodo che a differenza di altri algoritmi, che stimano l'APS dai segnali di fase srotolati, nella metodologia proposta la compensazione avviene direttamente sul dato arrotolato, in modo tale che la stima non è affetta da nessun potenziale errore di PhU. Gli esperimenti eseguiti su dati InSAR GB-SAR simulati e reali confermano la validità della tecnica proposta, confermando inoltre che il metodo è vantaggioso nelle zone caratterizzate da una forte escursione di quota (come ad esempio nelle regioni Alpine e montuose). Infine, viene presentata un'applicazione SAR interferometrica per la stima delle deformazioni della superficie investigata in tre dimensioni (3-D) attraverso l'uso congiunto ed integrato di dati SAR acquisiti da piattaforme satellitari e terrestri. Più precisamente, la catena di combinazione interferometrica sviluppata si compone anche degli innovativi algoritmi Mt-InSAR sviluppati in questo lavoro di tesi, al fine di ottenere mappe di velocità media di deformazione 3-D direttamente alla griglia spaziale più risoluta possibile. Inoltre, in conclusione, vengono menzionate anche alcune interessanti applicazioni SAR satellitari in ambito di prevenzione ed analisi di particolari fenomeni naturali e indotti dall'uomo.
Multi-temporal SAR interferometric (Mt-InSAR) techniques are nowadays mature tools to measure the temporal evolution of the Earth’s surface with millimetric accuracy. The reliability of crustal measurements is closely related to the goodness of the used Mt-InSAR algorithms in isolating the deformation-related signal from the overall signal, and this becomes increasingly complex as the noise levels of each interferogram increase. Canonical techniques are highly reliable in monitoring the displacement evolution of targets that are found to be largely stable or coherent over the entire period of analysis. Otherwise, when the scatterers are particularly affected by decorrelation problems, the obtained deformation estimates turn out to be corrupted and unreliable. Thus, there is a strong demand for new advanced Mt-InSAR processors that can provide accurate estimates of crustal deformation even in scenarios with more or less severe decorrelation problems. This thesis work focuses on the study of multi-temporal InSAR techniques applicable in both satellite and terrestrial case. Specifically, the canonical Mt-InSAR multigrid techniques for analyzing targets at the finest resolution grid will be discussed extensively highlighting their criticality in medium to low coherence areas, and in this context an innovative technique is proposed to better operate in decorrelated environments. The new method relies on efficient phase-unwrapping (PhU) operations performed at the native spatial scales. In particular, a set of multi-look (ML) interferograms is first unwrapped using conventional (or advanced) PhU algorithms at the regional scale. Subsequently, ML unwrapped interferograms are used to facilitate the PhU operations performed at the local scale (single-look). Specifically, the unwrapped multi-look interferograms are resampled to the single-look grid and modulo-2π subtracted to the single-look interferograms. These phase residuals are then unwrapped and added back to the multi-look resampled interferograms. To accomplish these operations, at variance with alternative multiscale methods, no (linear/nonlinear) models are used to fit the spatial high-pass phase residuals. Finally, the unwrapped single-look interferograms are properly inverted to retrieve the ground displacement time series using any small baseline (SB)-oriented multitemporal InSAR tool. Experimental results are performed by processing a set of SAR data acquired by the X-band COSMO-SkyMed sensor over the coastal area of Shanghai, China. Then, the focusing moves on the Weighted Least-squares (WLS) techniques applied within the InSAR framework for improving the performance of the phase unwrapping operations as well as for better conveying the inversion of sequences of unwrapped interferograms to generate ground displacement maps. In both cases, the identification of low-coherent areas, where the standard deviation of the phase is high, is requested. Therefore, a WLS method that extends the usability of the Mt-InSAR Small BAseline Subset (SBAS) algorithm in regions with medium-to-low coherence is presented. In particular, the proposed method relies on the adaptive selection and exploitation, pixel-by-pixel, of the medium-to-high coherent interferograms, only, so as to discard the noisy phase measurements. The selected interferometric phase values are then inverted by solving a WLS optimization problem. Noteworthy, the adopted, pixel-dependent selection of the “good” interferograms to be inverted may lead the available SAR data to be grouped into several disjointed subsets, which are then connected, exploiting the Weighted Singular Value Decomposition (WSVD) method. However, in some critical noisy regions, it may also happen that discarding of the incoherent interferograms may lead to rejecting some SAR acquisitions from the generated ground displacement time-series, at the cost of the reduced temporal sampling of the data measurements. Thus, variable-length ground displacement time-series are generated. The presented experiments have been carried out by applying the developed technique to a SAR dataset acquired by the COSMO-SkyMed (CSK) sensors over the Basilicata region, Southern Italy. In the continuation of the thesis work, the properties characterizing the phase non-closure of multi-look SAR interferograms are explored. Precisely, we study the implications of multi-look phase time incongruences on the generation of ground displacement time-series through SB Mt-InSAR methods. Our research clarifies how these phase inconsistencies can propagate through a time-redundant network of SB interferograms and contribute, along with PhU errors, to the quality of the generated ground displacement products. Moreover, we analyze the effects of short-lived phase bias signals that could happen in sequences of short baseline interferograms and propose a strategy for their mitigation. The developed methods have been tested using both simulated and real SAR data. The latter were collected by the Sentinel-1A/B (C-band) sensors over the study areas of Nevada state, U.S., and Sicily Island, Italy. After the development of algorithms for the satellite part, the work veers to ground-based SAR (GB-SAR) sensors. In this field, we propose a method for estimating and compensating the atmospheric phase screen (APS) in sets of SAR interferograms generated with a GB-SAR instrument. We address the presented approach’s physical, statistical, and mathematical framework by discussing its potential and limitations. In contrast with other existing algorithms that estimate the APS from the unwrapped phase signals, our methodology is based on the straightforward analysis of the wrapped phases, directly. Therefore, the method is not affected by any potential phase unwrapping mistake, and it is suitable for Mt-InSAR applications. The effects of the local topography, the decorrelation noise, and the ground deformation on the APS estimates are deeply studied. Experiments performed on simulated and real GB-SAR InSAR data corroborate the validity of the theory. In particular, the simulated results show that the method is beneficial in zones with medium-to-high topographic slopes (e.g., for Alpine and mountainous regions). Further, an interferometric SAR application for the study of three-dimensional (3-D) deformation through the joint and integrated use of satellite and ground SAR data is presented. More precisely, the interferometric data-combining technique exploits the innovative Mt-InSAR algorithms mentioned above, and allows obtaining 3-D mean displacement velocity maps at the finest spatial grid among the available data. In conclusion, also some interested satellite SAR applications in prevention and analysis of particular natural and human-induced disasters are given.

This report treats detection in IR-pictures taken from airplanes over the ground. The detection is divided in two parts. First there is a detection with filterkernels with the task to point on targets and objects that look like targets. The second part is a discriminator that demands more calculations and has the task to sort out the false alarms from the discriminator. Both the detector and the discriminator contain thresholds thats been trained from trainingsets of data. The results from the detector was better then expected hence it wasn’t possible to test the diskriminator properly.

Den här rapporten behandlar detektering i IR-bilder som är tagna från flygplan över marken. Detekteringen är i det här arbetet uppdelat i två delar. Först görs en detektering med filterkärnor som har till uppgift att peka ut mål och målliknande objekt. Den andra delen är en diskriminator som är något mer beräkningskrävande och har till uppgift att sortera bort de falskmål som detektorn fått med. Både detektorn och diskriminatorn innehåller trösklar som har tränats fram med träningsdata. Detektorn gav bättre resultat än väntat och diskriminatorn har därför inte kunnat testas ordentligt.

Wireless sensor networks are used in variety of applications including environmental monitoring, industrial control, healthcare, home automation, traffic control, and temperature and pressure monitoring systems. Many one-time use wireless micro sensor applications require ultra-low-power devices due to the limited energy capacity and lifetime of their small-size battery. Many sensor nodes require an analog-to-digital converter (ADC) to convert the analog output of the sensor to digital for storage and/or further processing. In this work, an 8-bit ultra-low-power successive approximation register (SAR) ADC is presented that operates from a low power supply voltage of 1V. The circuit is implemented in a 0.18 μm bulk CMOS technology without using any 10W-VT devices. In terms of active components, this ADC requires one comparator, 18 D flip-flops, several switches, and one voltage doubler. The ADC achieves an effective number of bits of 7, while operating with a sampling rate of 100kS/s and consuming 1.4 μW from a 1 V supply.

Multitemporal SAR images have been used successfully for the detection of different types of environmental changes. The detection of urban change using SAR images is complicated due to the special characteristics of SAR images—for example, the existence of speckle and the complex mixture of the urban environment. This thesis investigates the detection of urban changes using SAR images with the following specific objectives: (1) to investigate unsupervised change detection, (2) to investigate reduction of the speckle effect and (3) to investigate spatio-contextual change detection. Beijing and Shanghai, the largest cities in China, were selected as study areas. Multitemporal SAR images acquired by ERS-2 SAR (1998~1999) and Envisat ASAR (2008~2009) sensors were used to detect changes that have occurred in these cities. Unsupervised change detection using SAR images is investigated using the Kittler-Illingworth algorithm. The problem associated with the diversity of urban changes—namely, more than one typology of change—is addressed using the modified ratio operator. This operator clusters both positive and negative changes on one side of the change-image histogram. To model the statistics of the changed and the unchanged classes, four different probability density functions were tested. The analysis indicates that the quality of the resulting change map will strongly depends on the density model chosen. The analysis also suggests that use of a local adaptive filter (e.g., enhanced Lee) removes fine geometric details from the scene. Speckle suppression and geometric detail preservation in SAR-based change detection, are addressed using the nonlocal means (NLM) algorithm. In this algorithm, denoising is achieved through a weighted averaging process, in which the weights are a function of the similarity of small image patches defined around each pixel in the image. To decrease the computational complexity, the PCA technique is used to reduce the dimensionality of the neighbourhood feature vectors. Simple methods to estimate the dimensionality of the new space and the required noise variance are proposed. The experimental results show that the NLM algorithm outperformed traditional local adaptive filters (e.g., enhanced Lee) in eliminating the effect of speckle and in maintaining the geometric structures in the scene. The analysis also indicates that filtering the change variable instead of the individual SAR images is effective in terms of both the quality of the results and the time needed to carry out the computation. The third research focuses on the application of Markov random field (MRF) in change detection using SAR images. The MRF-based change detection algorithm shows limited capacity to simultaneously maintain fine geometric detail in urban areas and combat the effect of speckle noise. This problem has been addressed through the introduction of a global constraint on the pixels’ class labels. Based on NLM theory, a global probability model is developed. The iterated conditional mode (ICM) scheme for the optimization of the MAP-MRF criterion function is extended to include a step that forces the maximization of the global probability model. The experimental results show that the proposed algorithm is better at preserving the fine structural detail, effective in reducing the effect of speckle, less sensitive to the value of the contextual parameter, and less affected by the quality of the initial change map compared with traditional MRF-based change detection algorithm.

QC 20130610

Synthetic Aperture Radar (SAR) has been identified as a good candidate to provide high-resolution soil moisture information over extended areas. SAR data could be used as observations within a global Data Assimilation (DA) approach to benefit applications such as hydrology and agriculture. Prior to developing an operational DA system, one must tackle the following challenges of soil moisture estimation with SAR: (1) the dependency of the measured radar signal on both soil moisture and soil surface roughness which leads to an ill-conditioned inverse problem, and (2) the difficulty in characterizing spatially/temporally surface roughness of natural soils and its scattering contribution. The objectives of this project are (1) to develop a roughness measurement method to improve the spatial/temporal characterization of soil surface roughness, and (2) to investigate to what extent the inverse problem can be solved by combining multipolarization, multi-incidence, and/or multi-frequency radar measurements. The first objective is achieved with a measurement method based on Structure from Motion (SfM). It is tailored to monitor natural surface roughness changes which have often been assumed negligible although without evidence. The measurement method is flexible, a.ordable, straightforward and generates Digital Elevation Models (DEMs) for a SAR-pixel-size plot with mm accuracy. A new processing method based on band-filtering of the DEM and its 2D Power Spectral Density (PSD) is proposed to compute the classical roughness parameters. Time series of DEMs show that non-negligible changes in surface roughness can happen within two months at scales relevant for microwave scattering. The second objective is achieved using maximum likelihood fitting of the Oh backscattering model to (1) full-polarimetric Radarsat-2 data and (2) simulated multi-polarization / multi-incidence / multi-frequency radar data. Model fitting with the Radarsat-2 images leads to poor soil moisture retrieval which is related to inaccuracy of the Oh model. Model fitting with the simulated data quantifies the amount of multilooking for di.erent combinations of measurements needed to mitigate the critical e.ect of speckle on soil moisture uncertainty. Results also suggest that dual-polarization measurements at L- and C-bands are a promising combination to achieve the observation requirements of soil moisture. In conclusion, the SfM method along with the recommended processing techniques are good candidates to improve the characterization of surface roughness. A combination of multi-polarization and multi-frequency radar measurements appears to be a robust basis for a future Data Assimilation system for global soil moisture monitoring.

O presente trabalho apresenta uma metodologia para registro automático de imagens SAR interferométricas. Primeiramente as imagens SAR, no formato complexo, são registradas grosseiramente utilizando técnicas de correlação, que resultam em deslocamento em alcance e azimute, na escala de pixel, aplicados à segunda imagem, sem necessidade de interpolação. Opcionalmente pode ser aplicada a filtragem espectral em azimute nas imagens corregistradas, para a melhoria da coerência interferométrica entre elas. A segunda etapa do registro consiste na aplicação do registro fino, através de uma grade de pequenas janelas distribuídas de forma regular sobre cada uma das imagens, onde, para cada janela, é calculado o deslocamento fracionário (da ordem de subpixel) por correlação, resultando em uma grade de deslocamentos, de onde são calculados os polinômios de deformação nos sentidos de alcance e azimute, para a reamostragem da segunda imagem. A partir das imagens corregistradas pode-se aplicar opcionalmente a filtragem espectral no sentido de alcance, para a melhoria da coerência interferométrica entre elas. A qualidade do registro final pode ser avaliada através da análise da imagem de coerência e/ou pelo método dos resíduos aplicados na fase interferométrica gerada a partir das imagens corregistradas. Os algoritmos foram implementados em IDL/ENVI e testados em diversos conjuntos de dados.
This work presents an automatic registration method for interferometric SAR images. First the SAR images, in complex format, are coarse registered using correlation techniques. This results in range and azimuth shifts on a pixel scale, that are applied on the second image, without need for interpolation. Optionally the azimuth spectral filtering can be applied to the corregistered pair, to enhance the interferometric coherence between them. The second step is the fine registration. By using a grid of small regularly distributed windows over both images, a grid of subpixel shifts is calculated by correlation, from which deformation polynomial equations in range and azimuth are calculated and applied to resample the second image. Spectral range filtering can be optionally applied on the corregistered pair, to enhance interferometric coherence between them. The final registration quality can be measured by analysis of the coherence image and/or by residues method applied to the interferometric phase. The algorithms were implemented in IDL/ENVI and tested on many data.

The purpose of this project was the study of electrically small material coated antennas. In particular the use of a hybrid dielectric-ferrite material was examined, compared to dielectric alone, and ways it can improve antenna performance. The benefits resulting from the inclusion of ferrite were examined using both analytical and experimental methods. Initially a spherical analytical mathematical model was developed, to examine antenna efficiency, bandwidth and Specific Absorption Rate (SAR) in terms of different mixtures of relative permittivity εr and permeability μr. The theoretical model was then validated through a numerical transmission line matrix (TLM) simulation tool, applied to spherical and rectangular resonator geometries. It was observed that a material with equal values of relative permittivity and permeability in combination with specific positioning of the antenna in relation to the head, can give rise to the definitive small-size, high-efficiency, high-bandwidth, low-SAR antenna.

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Ce travail decrit d'abord le principe du sar (radar a synthese d'ouverture) et le traitement des donnees, dans le cas ideal d'un radar se deplacant avec un mouvement rectiligne uniforme. Puis sont exposes les differents mouvements parasites, ainsi qu'une evaluation de leur importance. Ensuite on presente des methodes de compensation de mouvements sans apport d'information exterieure (du type autofocus). Une methode qui utilise des donnees trajectographiques pour compenser les mouvements est ensuite proposee. Un simulateur de donnees brutes sar (limite a quelques points brillants) a ete developpe, permettant de mesurer l'effet des mouvements et l'apport de la compensation. Cette compensation est finalement appliquee a des donnees reelles

Cette thèse s'inscrit dans le cadre des travaux menés en télédétection pour le suifi et la discrimination des régions naturelles. Par rapport aux instruments optiques, les systèmes radar permettent d'acquérir des informations complémentaires. Or, l'analyse de l'information contenue dans le signal, et l'étude des caractéristiques physiques des régions imagées nécessite la reconnaissance, sur l'image, des différentes catégories de cibles, présentant différentes propriétés de rétrodiffusion. Le but de la classification est alors de fournir des images où l'information est résumée et qui sont donc plus lisibles (notamment sans speckle). Le travail effectué a porté sur le développement d'algorithmes de classification appliqués aux images SAR polarimétriques, la validation des méthodes et des algorithmes proposés, ainsi que l'étude de leur robustesse. Plus précisément, nous nous sommes intéressés aux méthodes non supervisées pour leurs avantages suivants : caractère automatique, possibilité de séparer et d'estimer les caractéristiques de classes inconnues a priori, et surtout obtention de résultats correspondant à l'information réellement présente dans l'image (c'est-à-dire, en particulier, non biaisés par des informations extérieures introduites a priori). Outre le choix d'un vecteur caractéristique (adapté aux images SAR polarimétriques dans notre cas), la mise oeuvre de méthodes de classification non supervisées suppose la définition d'un modèle mathématique de l'image, pour lequel nous avons distingué deux cas : • celui de données «homogènes», c'est-à-dire pour lesquelles nous avons pu définir une même loi de distribution conditionnellement aux classes, et qui fut le cas des données monobandes. Dans le cas de images SAR, le critère de robustesse des estimateurs (de la classification non supervisée) est d'autant plus crucial que la présence de speckle nuit à la qualité de ces estimateurs. L'alborithme préconisé est alors le suivant : estimation des caractéristiques des classes par le fuzzy c-means, puis classification de l'image selon le Maximum A Posteriori. Cet algorithme a ensuite été appliqué au problème du choix de filtres de speckle utilisés en prétraitement de l'image, et au problème de la détermination des fréquences et des polarisations optimales pour la détection des cultures, et de la quantification de l'apport d'information dû à la prise en compte de termes supplémentaires. • celui de données hétérogènes (non modélisables par une même loi de distribution), telles que les images fournies par différents capteurs (multibande radar, optique). Tout d'abord, la complémentarité des images SAR multifréquences et optique-radar a été étudiée. Pour cela, la mesure de redondance définie par Shannon a été appliquée au niveau des classes, ce qui a permis de prendre en compte à la fois l'information radiométrique et celle spatiale. Ensuite, un algorithme de fusion de données, non supervisé, fondé sur la théorie des croyances de Dempster-Shafer a été proposé. Ses performances vis-à-vis de méthodes de fusion simples ont été quantifiées, et il a été validé sur plusieurs jeux de données, correspondant à différents sites (Orgeval, France, Feltwell, Royaume Uni, la Bretagne), et différents capteurs radar ou optiques (AirSAR, SIR-C, Thematic Mapper Simulator, NOAA-AVHRR). Le travail de thèse représente donc une contribution au développement de méthodes d'analyse des données SAR polarimétriques monobandes, multibandes , ou utilisées en synergie avec des données visible/infrarouge.

This Engineering Doctorate concerns the enhancement and detection of slow-moving targets in SAR images. Moving targets are incorrectly located or not captured at all in SAR images. Slow-moving targets within the clutter-Doppler-band appear at incorrect locations within the SAR image. Detecting these slow targets would have broad applications in defence surveillance, traffic monitoring and perimeter protection. As an industrially motivated project, partnered with Selex ES, this work goes beyond the explanation and confirmation of theories and looks at the practicality of implementing techniques. The goal of the research is to develop algorithms with general applicability that can also be specifically exploited on current Selex ES SAR systems. Additionally, the benefit of larger numbers of channels should be evaluated to help guide future product development. After finding the capabilities of single channel SAR to be limited to the detection of very bright targets, the main focus of the research is the use of multiple spatial channels to improve moving target capabilities. A multichannel SAR simulator has been developed that, along with multiple flight trials with the PicoSAR radar system, provides data sets that are used to develop and test the algorithms presented in this work. A theoretical background is given that includes analysis of deramp-on-receive processing, multichannel SAR image formation and the Selex ES PicoSAR system. Also included is a novel derivation of the effects of moving targets in spotlight SAR imagery that confirms previous results without the previous approximations. The derivation uses an entirely new approach that considers the closing velocity of moving targets rather than explicit analysis of the signal phases. The main thrust of the research looks at image-domain exploitation of dual channel SAR to suppress stationary clutter and enhance the returns from moving targets. Adaptive channel alignment is used to calibrate and align multiple channels such that the magnitude and phase differences between the channels can be used to cancel stationary clutter contributions. After this clutter suppression, the velocity of bright targets can be then estimated so that they can be correctly focused and positioned within the SAR image. In the more common case where moving targets remain dim after clutter suppression, a third channel is needed to estimate target velocity. Simulated data is used to demonstrate clutter suppression interferometry as a technique to achieve this. The use of real data throughout all of these considerations leads to the conclusion that current dual-channel radar systems such as PicoSAR can be used to detect dim, slow-moving targets. To correct the motion-induced degradation of these targets, it will be necessary to have a third spatial channel but significant gains can be made with only two.

No território brasileiro há muitas áreas não cobertas por cartas topográficas e as existentes encontram-se desatualizadas devido às contínuas alterações de uso e cobertura do solo. O Sistema de Proteção da Amazonia (SIPAM) dispoe de aeronaves equipadas com radar de abertura sintética que permitem o imageamento em condições adversas. Este radar foi concebido para tarefas de reconhecimento, sob uma perspectiva civil e militar. O potencial deste sensor para fins cartográficos ainda nao foi explorado. O objetivo desta dissertação é avaliar altimetricamente o modelo digital do terreno interferométrico fornecido pelo SIPAM. Para atingir este propósito, foi realizada uma investigação de possíveis fatores que afetam a qualidade do modelo obtido por interferometria, tais como o gradiente de declividade, o aspecto, as regioes da imagem na dimensao em alcance, os usos e coberturas do solo. A área de estudo, localizada no Município de Sao José dos Campos, Estado de São Paulo, Brasil foi dividida em regioes homogeneas (estratos), cujas características estavam associadas aos fatores que poderiam afetar a qualidade do modelo. As coletas de amostras nos estratos foram realizadas com o emprego de receptores GPS utilizando os métodos de posicionamento relativo (levantamento de pontos amostrados) e diferencial (levantamento de vias terrestres). O modelo digital do terreno apresentou erros planimétricos, tendo sido corrigido com as vias terrestres medidas como referencia. O modelo digital do terreno corrigido foi classificado em relação às normas cartográficas vigentes, atendendo a escala de 1:100.000 (classe A) do Padrão de Exatidao Cartográfica, com a condição de que a tendencia seja removida. Os erros do modelo digital do terreno corrigido apresentaram uma componente global de tendencia, com um erro médio de -27,83 m. Os estratos apresentaram uma quantidade reduzida de pontos amostrados, sendo empregada a estatística não-paramétrica. Após a remoção da tendência, os erros dos estratos nao apresentaram, em geral, diferenças significativas entre as regioes em alcance, nem entre os usos e coberturas do solo. O aspecto e o gradiente de declividade foram considerados fatores influentes nos erros. Os estratos montanhosos apresentam uma maior variabilidade, tendo o estrato montanhoso com aspectos frontal e anti-azimutal uma tendencia a subestimar as altitudes. O estrato ondulado com aspectos dorsal e azimutal tende a superestimar as altitudes, com média variabilidade. O estrato formado pelo agrupamento do ondulado com aspectos frontal e anti-azimutal e do plano nao apresenta tendencia, com baixa variabilidade. O estrato montanhoso com aspectos dorsal e anti-azimutal apresenta alta variabilidade e tendencia nula. Apesar do SAR R-99B apresentar uma alta resolução espacial no modo interferométrico (3 m), o modelo digital do terreno extraído nao atendeu às escalas altimétricas maiores que 1:100.000 (classe A), resultado aquém do esperado, e apresentou um erro planimétrico de 178,297 m, o que inviabiliza a sua utilização em cartografia, caso não seja realizada previamente uma corre¸cao geométrica apropriada e a remoção da tendência.
In the Brazilian territory there are several areas with no topographic mapping coverage and the existent maps are not updated due to the continuous land use and land cover changes. The Sistema de Prote¸cao da Amazonia (SIPAM) uses airplanes with synthetic aperture radar which allows to image in several conditions. This radar was designed for recoinassance tasks with a civil and military perspective. The potential of this sensor for mapping has not been studied yet. The purpose of this dissertation was to evaluate the elevations of the interferometric digital terrain model supplied by SIPAM. To reach this aim, it was analyzed the possible factors wich affect the quality of the model extracted by interferometry such as the slope gradient, the aspect, the regions of imagery in range dimension, the land use and land cover. The study site at Sao Jos´e dos Campos, state of Sao Paulo, Brazil was divided in homogeneous regions (strata) which features were related to the factors that would affect the quality of the model. The sample collection in the strata were done with the GPS receivers performing relative positioning (sample points survey) and differential GPS (road survey). The digital terrain model showed shift and rotation problems that were fixed using the surveyed roads as reference. The fixed digital terrain model was classified according to the Brazilian mapping standards as compatible at scale of 1:100.000 (class A) on condition that bias will be removed. The digital terrain model errors have bias, with a mean error of -27,83 m. The strata had a small number of samples being used the nonparametric statistics. After the remotion of bias, the strata did not have significant differences at the regions of imagery in range dimension and at the land use and land cover, in general. The aspect and slope gradient were considered influential on errors. The mountain strata showed a larger variability and the mountain stratum with foreslope and anti-azimuthal aspects tend to underestimate the errors. The ondulated stratum with backslope and azimuthal aspects tend to overestimate the errors with intermediate variability. The stratum composed by grouping the ondulated with foreslope and anti-azimuthal aspects and flat does not show bias and it has intermediate variability. Although the SAR R-99B has a high spatial resolution in interferometric mode (3 m), the digital terrain model extracted was not compatible with scales higher than 1:100.000 (class A), with a result worse than the expected and had a planimetric error of 178,297 m that does not allow its use for mapping unless it is applied first an appropriate geometric correction and bias removal.

In recent years, there has been a growing need for Successive Approximation Register (SAR) Analog-to-Digital Converter in medical application such as pacemaker. The demand for long battery life-time in these applications poses the requirement for designing ultra-low power SAR ADCs. This thesis work initially investigates and compares different structures of SAR control logics including the conventional structures and the delay line based controller. Additionally, it focuses on selection of suitable dynamic comparator architecture.  Based on this analysis, dynamic two-stage comparator is selected due to its energy efficiency and capability of working in low supply voltages. Eventually, based on these studies an ultra-low power 10-bit SAR ADC in 65 nm technology is designed. Simulation results predict that the ADC consumes 12.4nW and achieves an energy efficiency of 14.7fJ/conversion at supply voltage of 1V and sampling frequency of 1kS/s. It has a signal-to-noise-and-distortion (SINAD) ratio of 60.29dB and effective-number-of-bits (ENOB) of 9.72 bits. The ADC is functional down to supply voltage of 0.5V with proper performance and minimal power consumption of 6.28nW.

Los radares de apertura sintética basados en tierra (GB-SAR) son instrumentos que, aun siendo relativamente jóvenes, se utilizan con éxito para monitorizar operacionalmente deslizamientos de tierra. Por otra parte, el manto nivoso se ha estudiado tradicionalmente a nivel local con sensores invasivos o con radares de onda continua. El trabajo presentado en esta tesis contribuye a la conjunción de ambos campos: el uso de sensores GB-SAR para la monitorización del manto nivoso. En los capítulos 5, 6 y 7 se muestran las tres técnicas desarrolladas: cálculo de la altura del manto nivoso, cálculo del volumen de nieve desplazado en una avalancha, y detección y clasificación de avalanchas.
La altura del manto nivoso se calcula a partir de la fase interferométrica diferencial de dos adquisiciones SAR consecutivas bajo la hipótesis de nieve seca y asumiendo un modelo de nieve de una capa. El volumen desplazado en una avalancha se obtiene mediante la resta de dos modelos del terreno digitales (DTM) generados justo antes y después del fenómeno avalancha. Los DTMs se obtienen con el modo topográfico del instrumento: dos antenas separadas una cierta distancia reciben simultáneamente los ecos de una tercera antena que transmite. La tercera técnica de monitorización, detección y clasificación de avalanchas, se realiza mediante la magnitud de la coherencia compleja entre dos imágenes SAR consecutivas. Las avalanchas de nieve presentan valores de coherencia muy bajos en el área afectada, que puede ser identificada mediante un modelo basado en características morfológicas y estadísticas. En la presente tesis se presenta un innovador algoritmo para la detección y clasificación de avalanchas.
El GB-SAR del Joint Research Centre, una vez mejorado para permitir su uso continuado 24h al día y 7 días a la semana (capítulo 3), ha sido utilizado para desarrollar y verificar las técnicas mencionadas anteriormente. Se han realizado medidas durante seis inviernos, que han proporcionado más de 120000 imágenes SAR a una frecuencia aproximada de 12 minutos por imagen. Se han estudiado dos emplazamientos, cada uno con características diferentes con el fin de verificar el uso operativo de las técnicas bajo condiciones reales. Los resultados muestran que la obtención de la altura del manto nivoso es posible pero su aplicación está limitada al campo experimental ya que su uso está condicionado por fuertes restricciones. Un estudio de viabilidad posteriormente confirmado con medidas muestra, en cambio, las limitaciones de precisión de los instrumentos GB-SAR para obtener una estima del volumen de nieve desplazado en una avalancha. Finalmente, la técnica más prometedora es la de detección y clasificación de avalanchas, la cuál se demuestra factible y robusta desde un punto de vista operativo y práctica desde una perspectiva de usuario final.
Ground-based synthetic aperture radars (GB-SAR) are instruments that, although relatively young, are operationally used to monitor landslides with sub-millimetre accuracy. There are however other application fields that deserve some attention.
Monitoring of the snow cover and, in particular, of those processes associated with the snow avalanches are a clear example of this. To date, monitoring of the snow cover has been traditionally carried out at local scale either with invasive sensors or with continuous wave (CW) radars, while at wider scales air- or satellite-borne sensors have been employed. The work presented in this PhD thesis is a first attempt to study the potential use of GB-SAR sensors to monitor the snow cover. Three techniques for monitoring snow cover with GB-SAR are presented through Chapters 5, 6 and 7: snow height retrieval, snow avalanche volume retrieval and avalanche events detection and classification.
Snow height is retrieved by using the differential interferometric phase of two consecutive SAR acquisitions under the assumption of single layer model and dry snow conditions. The volume displaced in a snow avalanche is computed by subtracting two digital terrain models (DTM) generated immediately before and after the avalanche event.
DTMs are obtained with the topographic interferometric mode of the instrument: a spatial base line separates two antennas that simultaneously receive the echoes of a third transmitting antenna. The third monitoring technique, avalanche detection and classification, is achieved identifying low-coherence anomalies in the coherence image between two successive SAR acquisitions. Snow avalanches present a low-coherence signature that can be identified by a morphological and statistical parameter model. A novel detection and classification scheme for snow avalanches is proposed.
The Joint Research Centre's GB-SAR sensor, upgraded to allow continuou operation 24 hours a day 7 days a week, also as part of the work of this thesis (Chapter 3), was used to develop and assess the before mentioned techniques. Measurements were carried out during six winters, providing more than 120000 SAR images at a rate of one image every 12 minutes approximately. Two test sites were studied, each with different characteristics in order to assess under real conditions the operational use of the monitoring techniques. Results show that snow height retrieval is achievable but remains, for the moment, an on-going research topic due to strong constraints limiting its use. A feasibility study is presented showing the accuracy limitations of GB-SAR to compute the snow volume involved in an avalanche. Finally, the most promising technique is snow avalanche detection and classification, which is demonstrated to be feasible and robust from an operational point of view and practical from an end user perspective.

Space-borne Synthetic Aperture Radar (SAR) systems have demonstrated great effectiveness to survey wide areas, independently of the weather conditions and the day/night cycle. One of the most exploited applications is Differential SAR Interferometry (DInSAR), and by extension, advanced multi-temporal techniques addressed as Persistent Scatterers Interferometry (PSI). These techniques provide the means to retrieve the displacement on the observed terrain surface. Taking advantage of the high coverage provided by this technology, natural and human induced phenomena may be monitored and detected in order to avoid and prevent hazardous or even catastrophic situations. A good characterization of such events is often related to the density and quality of the information delivered. In many cases, the success in the interpretation of localized surface motion phenomena relies on having as much measurements as possible. Conventional insitu techniques, when used properly, are able to provide reliable measurements. However, they are limited to their localization, and deploy a high number of instruments is not cost effective. The good characterization provided by PSI measurements is limited by the acquisition parameters and the actual scene under monitoring. SAR images sensitivity over the scene depends strongly on the geometric shape and distribution of targets. Historically, satellite SAR sensors had single polarimetric capabilities, so sensitivity over the scene was restricted to a certain antenna configuration. On the contrary, polarimetric acquisitions emit an receive with different antenna configurations, providing sensitivity to different geometries in the scenario. The launch in these later years of several satellites with polarimetric capabilities has triggered its use in several fields of application. The objective of this thesis is to evaluate the use of Polarimetric SAR (PolSAR) data for its application in the PSI framework. The extra information contained in PolSAR datasets is bound to improve the effectiveness of PSI techniques. Obtaining a higher density and quality of motion measurements will ease the detection and interpretation of terrain displacement phenomena.
Els Radars d'Obertura Sintètica (SAR) embarcats en satèl·lits han demostrat ser molt efectius per monitoritzar grans àrees, independentment de les condicions atmosfèriques i del cicle dia/nit. L'aplicació més explotada es l'Interferometria Diferencial SAR (DInSAR), i per extensió, les tècniques avançades de processament multi-temporal anomenades Interferometria de Reflectors Persistents (PSI). Aquestes tècniques són capaces de mesurar el desplaçament en superfície del terreny observat. Aprofitant la gran cobertura que s'aconsegueix amb aquesta tecnologia, fenòmens d'origen tant natural com humà poden ser detectats i controlats per evitar i prevenir situacions de perill o fins i tot catastròfiques. La bona caracterització d'aquestes situacions sovint es relaciona tant amb la densitat com en la qualitat de la informació obtinguda. En molts casos, l’èxit en la interpretació de moviments de terreny localitzats depèn de tenir tants punts de mesura com sigui possible. Les tècniques convencionals de mesura in-situ, quan s'usen de forma adequada, són capaces de donar mesures fiables. No obstant, la seva cobertura està limitada a la localització de l'instrument, i la instal·lació d’un gran nombre d'instruments no és una solució econòmica. La bona caracterització de l'àrea mesurada amb tècniques PSI està limitada pels paràmetres d'adquisició i les característiques de la pròpia escena observada. La sensitivitat de les imatges SAR depèn en gran mesura de la distribució i la forma geomètrica dels blancs mesurats. Històricament, els sensors SAR emetien en polarització simple, i per tant la sensitivitat a la escena estava restringida a aquesta configuració específica de la antena. Per altra banda, durant les adquisicions polarimètriques s'emet i es rep en diferents configuracions de l'antena. Això permet tenir sensitivitat a geometries diferents dins la mateixa escena. El llançament aquest últims anys de diferents satèl·lits amb capacitats polarimètriques ha permès el seu ús en diversos camps d'aplicació. L'objectiu d’aquesta tesi és avaluar l'ús de dades polarimètriques SAR (PolSAR) per la seva aplicació en el marc de les tècniques PSI. La informació addicional que contenen els conjunts d’adquisicions PolSAR ha de millorar l'efectivitat de les tècniques PSI. L'obtenció d'una millor densitat i qualitat de les mesures permet una millor detecció i interpretació dels fenòmens de desplaçament superficial del terreny.

In the scope of this thesis, simulation-based analyses and comparative evaluation of Synthetic Aperture Radar (SAR) image formation techniques, namely Time Domain Correlation, Range Stacking, Range Doppler and Chirp Scaling algorithms, are presented. For this purpose, first, the fundamental concepts of SAR such as SAR geometry, resolution and signal properties are explained. A broadside SAR simulator that provides artificial raw data as an input to the algorithms is designed and implemented. Then, the mathematical background of the imaging algorithms discussed in the thesis is provided. Implementations of these algorithms and simulations are carried out using MATLAB®
. Finally, simulation results are presented and discussed to show the advantages and disadvantages of the algorithms.

The recognition of discrete man-made targets in remotely sensed imagery is an important problem for strategic and tactical applications. The objective of this thesis is to examine whether the extra information content in polarimetric radar imagery will overcome the difficult problems in remotely sensed Synthetic Aperture Radar (SAR) data and improve target recognition capabilities with respect to single channel SAR. In conventional SAR these problems are mainly the result of speckle and receiver noise adversely affecting the limited information available in the single channel of data. To meet this objective, target samples from different target classes have been identified in real, polarimetric SAR data. These targets have a strong backscatter relative to the background clutter and are about three to six pixels in size. Target classes are denned by their polarization signature and available ground truth data. By exploiting the polarimetric properties of these targets it is possible to demonstrate an improvement in target detectability. A large number of measurements extracted from the polarimetric properties of scatterers are examined and reduced sets of these features have been selected. To discriminate identified targets in a SAR image, a supervised classification algorithm has been implemented. Optimal weighting of the feature sets to improve classification was not implemented due to the low confidence placed on the target feature distribution estimates as a result of the sparse training set. However, a comparison of classification results using the polarimetric data with trials performed on single channel SAR data synthesized from the same data set, clearly demonstrates a significant performance benefit of polarimetric radar. A polarimetric target model has been developed to estimate the sensitivity of the polarimetric classifier to several of the adverse properties of SAR polarimetry. Throughout this thesis, the observations are compared with other current research in this area and several related conclusions can be reached.
Applied Science, Faculty of
Electrical and Computer Engineering, Department of
Graduate

Multitemporal SAR images have been increasingly used for the detection of different types of environmental changes. The detection of urban changes using SAR images is complicated due to the complex mixture of the urban environment and the special characteristics of SAR images, for example, the existence of speckle. This thesis investigates urban change detection using multitemporal SAR images with the following specific objectives: (1) to investigate unsupervised change detection, (2) to investigate effective methods for reduction of the speckle effect in change detection, (3) to investigate spatio-contextual change detection, (4) to investigate object-based unsupervised change detection, and (5) to investigate a new technique for object-based change image generation. Beijing and Shanghai, the largest cities in China, were selected as study areas. Multitemporal SAR images acquired by ERS-2 SAR and ENVISAT ASAR sensors were used for pixel-based change detection. For the object-based approaches, TerraSAR-X images were used. In Paper I, the unsupervised detection of urban change was investigated using the Kittler-Illingworth algorithm. A modified ratio operator that combines positive and negative changes was used to construct the change image. Four density function models were tested and compared. Among them, the log-normal and Nakagami ratio models achieved the best results. Despite the good performance of the algorithm, the obtained results suffer from the loss of fine geometric detail in general. This was a consequence of the use of local adaptive filters for speckle suppression. Paper II addresses this problem using the nonlocal means (NLM) denoising algorithm for speckle suppression and detail preservation. In this algorithm, denoising was achieved through a moving weighted average. The weights are a function of the similarity of small image patches defined around each pixel in the image. To decrease the computational complexity, principle component analysis (PCA) was used to reduce the dimensionality of the neighbourhood feature vectors. Simple methods to estimate the number of significant PCA components to be retained for weights computation and the required noise variance were proposed. The experimental results showed that the NLM algorithm successfully suppressed speckle effects, while preserving fine geometric detail in the scene. The analysis also indicates that filtering the change image instead of the individual SAR images was effective in terms of the quality of the results and the time needed to carry out the computation. The Markov random field (MRF) change detection algorithm showed limited capacity to simultaneously maintain fine geometric detail in urban areas and combat the effect of speckle. To overcome this problem, Paper III utilizes the NLM theory to define a nonlocal constraint on pixels class-labels. The iterated conditional mode (ICM) scheme for the optimization of the MRF criterion function is extended to include a new step that maximizes the nonlocal probability model. Compared with the traditional MRF algorithm, the experimental results showed that the proposed algorithm was superior in preserving fine structural detail, effective in reducing the effect of speckle, less sensitive to the value of the contextual parameter, and less affected by the quality of the initial change map. Paper IV investigates object-based unsupervised change detection using very high resolution TerraSAR-X images over urban areas. Three algorithms, i.e., Kittler-Illingworth, Otsu, and outlier detection, were tested and compared. The multitemporal images were segmented using multidate segmentation strategy. The analysis reveals that the three algorithms achieved similar accuracies. The achieved accuracies were very close to the maximum possible, given the modified ratio image as an input. This maximum, however, was not very high. This was attributed, partially, to the low capacity of the modified ratio image to accentuate the difference between changed and unchanged areas. Consequently, Paper V proposes a new object-based change image generation technique. The strong intensity variations associated with high resolution and speckle effects render object mean intensity unreliable feature. The modified ratio image is, therefore, less efficient in emphasizing the contrast between the classes. An alternative representation of the change data was proposed. To measure the intensity of change at the object in isolation of disturbances caused by strong intensity variations and speckle effects, two techniques based on the Fourier transform and the Wavelet transform of the change signal were developed. Qualitative and quantitative analyses of the result show that improved change detection accuracies can be obtained by classifying the proposed change variables.

QC 20150529

Depuis plus de vingt ans, les altimètres classiques comme Topex, Poseidon-2 ou Poséidon-3, ont fourni des formes d'onde qui sont utilisées pour estimer de nombreux paramètres tels que la distance entre le satellite et la scène observée, la hauteur des vagues et la vitesse du vent. L'amélioration de la qualité des paramètres altimétriques a nécessité le développement de plusieurs modèles d'échos et d'algorithmes d'estimation paramétrique. Par ailleurs, un grand effort est récemment dédié au traitement des échos côtiers afin d'analyser les mesures altimétriques le plus près possible des côtes. Cette thèse s'intéresse à la résolution de ces deux problèmes, à savoir, le traitement des formes d'onde côtières et l'amélioration de la qualité des paramètres océaniques estimés. La première partie de l'étude traite le problème des formes d'onde côtières en proposant un nouveau modèle altimétrique tenant compte de la présence éventuelle d'un pic sur l'écho altimétrique. Dans la seconde partie de notre travail, nous nous sommes intéressés à l'étude de l'altimétrie SAR/Doppler. Cette nouvelle technologie vise à réduire le bruit de mesure et à augmenter la résolution le long de la trace par rapport à l'altimétrie conventionnelle. Deux modèles altimétriques ont été développés afin d'estimer les paramètres associés aux échos SAR/Doppler. Ces modèles montrent une nette amélioration de la qualité des paramètres estimés par rapport à l'altimétrie conventionnelle.