Quelles sont les particules élémentaires et comment l'univers proviennent sont les principales forces motrices de la physique des hautes énergies. Afin de démontrer le modèle standard et découvrez la nouvelle physique, plusieurs détecteurs sont construits pour les expériences en physique des hautes énergies. Capteurs à pixels CMOS offrent un compromis attirant entre la vitesse de lecture, le budget matériel, la tolérance au rayonnement, la consommation d'énergie et la granularité, par rapport aux capteurs à pixels hybrides et des dispositifs à transfert de charge. Ainsi, les CPS sont un bon choix pour détecter les particules chargées dans les détecteurs de vertex et des télescopes de faisceau. La distribution de puissance devient un enjeu important dans les détecteurs à venir, puisque une quantité considérable de capteurs seront installés. Malheureusement, le «Independent Powering» échoue, comme l'approche traditionnelle. Afin de résoudre les problèmes de distribution de puissance et de fournir des tensions silencieuses, cette thèse se concentre sur la conception de la gestion de l'alimentation à faible bruit, à basse consommation d'énergie, de petite taille et sur-puce pleinement pour les CPS. Les CPS sont d'abord introduits en tirer les exigences de conception de la gestion de l'alimentation. La distribution de puissance dédiées à les CPS est ensuite proposé, dans laquelle la gestion de l'alimentation est utilisée comme seconde étape de conversion de puissance. Deux régulateurs sur-puce pleinement sont proposés pour générer la tension d'alimentation analogique et de la tension d'alimentation de référence requis par l'opération d'échantillonnage double corrélé, respectivement. Deux prototypes ont vérifié ces régulateurs. Ils peuvent répondre aux exigences des CPS. En outre, les techniques de gestion de l'alimentation et de la conception tolérance au rayonnement sont également présentés dans cette thèse. / What are the elementary particles and how did the universe originate are the main driving forces in the high energy physics. In order to further demonstrate the standard model and discover new physics, several detectors are built for the high energy physics experiments. CMOS pixel sensors (CPS) can achieve an attractive tradeoff among many performance parameters, such as readout speed, granularity, material budget, power dissipation, radiation tolerance and integrating readout circuitry on the same substrate, compared with the hybrid pixel sensors and charge coupled devices. Thus, the CPS is a good candidate for tracking the charged particles in vertex detectors and beam telescopes.The power distribution becomes an important issue in the future detectors, since a considerable amount of sensors will be installed. Unfortunately, the independent powering has been proved to fail. In order to solve the power distribution challenges and to provide noiseless voltages, this thesis focuses on the design of a low noise, limited area, low power consumption and full on-chip power management in CPS chips. The CPS are firstly introduced drawing the design requirements of the power management. The power distribution dedicated to CPS chips is then proposed, in which the power management is utilized as the second power conversion stage. Two full on-chip regulators are proposed to generate the analog power supply voltage and the reference voltage required by correlated double sampling operation, respectively. Two prototypes have verified these regulators. They can meet the requirements of CPS. Moreover, the power management techniques and the radiation tolerance design are also presented in this thesis.

[pt] Câmeras de pixel único consistem em reconstruir computacionalmente imagens em duas dimensões a partir de um conjunto de medidas feitas por um detector de único pixel. Para que se obtenha a informação espacial, um conjunto de padrões de modulação são aplicados à luz transmitida/refletida do objeto e essa informação é combinada com o sinal integral do detector. Primeiro, apresentamos uma visão geral desses sistemas e demonstramos a implementação de uma prova de conceito capaz de fazer aquisição de imagem usando três modos de operação: Varredura, escaneamento por base de Hadamard, e escaneamento por base de Hadamard com sensoriamento compreensivo. Segundo, discutimos como os diferentes parâmetros experimentais do sistema ótico afetam a aquisição. Finalmente, comparamos a performance dos três modos de operação quando usados para a aquisição de images com tamanhos entre (8px, 8px) e (128px, 128px). / [en] Single-pixel imaging consists in computationally reconstructing 2-dimensional images from a set of intensity measurements taken by a singlepoint detector. To derive the spatial information of a scene, a set of modulation patterns are applied to the transmitted/backscattered light from the object and combined with the integral signal on the detector. First, we present an overview of such optical systems and implement a proof of concept that can perform image acquisition using three different modes of operation: Raster scanning, Hadamard basis scanning, and Hadamard compressive sampling. Second, we explore how the different experimental parameters affect image acquisition. Finally, we compare how the three scanning mode perform for acquisition of images of sizes ranging from (8px, 8px) to (128px, 128px).

This thesis is about simulation of semiconductor X-ray and particledetectors. The simulation of a novel coating for solid state neutrondetectors is discussed as well as the implementation of a simulationframework for hybrid pixel detectors.Today’s most common thermal neutron detectors are proportionalcounters, that use 3He gas in large tubes or multi wire arrays. Globalnuclear disarmament and the increase in use for homeland securityapplications has created a shortage of the gas which poses a problemfor neutron spallation sources that require higher resolution and largersensors. In this thesis a novel material and clean room compatible pro-cess for neutron conversion are discussed. Simulations and fabricationhave been executed and analysed in measurements. It has been proventhat such a device can be fabricated and detect thermal neutrons.Spectral imaging hybrid pixel detectors like the Medipix chipare the most advanced imaging systems currently available. Thesechips are highly sophisticated with several hundreds of transistors perpixel to enable features like multiple thresholds for noise free photoncounting measurements, spectral imaging as well as time of arrivalmeasurements. To analyse and understand the behaviour of differentsensor materials bonded to the chip and to improve development offuture generations of the chip simulations are necessary. Generally, allparts of the detector system are simulated independently. However, itis favourable to have a simulation framework that is able to combineMonte Carlo particle transport, charge transport in the sensor as wellas analogue and digital response of the pixel read-out electronics. Thisthesis aims to develop such a system that has been developed withGeant4 and analytical semiconductor and electronics models. Further-more, it has been verified with data from measurements with severalMedipix and Timepix sensors as well as TCAD simulations.Results show that such a framework is feasible even for imagingsimulations. It shows great promise to be able to be extended withfuture pixel detector designs and semiconductor materials as well asneutron converters to aim for next generation imaging devices.

In current particle physics field, the progressive detection technologies are used. The pixel detectors are one of them. These detectors are divided into small subdetectors (pixels), which allow viewing exact tracks of the detected particles. This thesis defines criteria for mathematical description of the shape of the particle tracks of different kinds (e-, γ, p, α, μ) and compares several methods used for a classification -neural networks, decision trees and others. The Pixa software was implemented to process the data measured by pixel detectors. This software implements the characteristics and classification methods and creates statistical and other physical results.

In this effort a new measurement technique for the lateral Goos-Hanchen shift is developed, analyzed, and demonstrated. The new technique uses classical image formation methods fused with modern detection and analysis methods to achieve higher levels of sensitivity than obtained with prior practice. Central to the effort is a new mathematical model of the dispersion seen at a step shadow when the Goos-Hanchen effect occurs near critical angle for total internal reflection. Image processing techniques are applied to measure the intensity distribution transfer function of a new divergence model of the Goos-Hanchen phenomena providing verification of the model. This effort includes mathematical modeling techniques, analytical derivations of governing equations, numerical verification of models and sensitivities, optical design of apparatus, image processing

The performance of a dedicated A/D converter located beneath each pixel is explored in this thesis. Specifically, a voltage to frequency converter coupled with a direct injection amplifier designed for use with an IR focal plane array is analyzed. This versatile implementation of a Readout Integrated Circuit can be found applicable to a wide variety of imaging technologies. Noise performance of the conversion system is theoretically calculated, and is supported by SPICE simulations using valid CMOS SPICE models. It is shown that a 10 transistor sub-pixel voltage to frequency analog to digital converter will produce noise that is less than the input shot noise. Design considerations will be addressed to ensure continued performance as the scale of the imagers increase to large format arrays.

O monitoramento do meio ambiente e suas mudanças requer a análise de uma grade quantidade de imagens muitas vezes coletadas por satélites. No entanto, variações nos sinais devido a mudanças nas condições atmosféricas frequentemente resultam num deslocamento da distribuição dos dados para diferentes locais e datas. Isso torna difícil a distinção dentre as várias classes de uma base de dados construída a partir de várias imagens. Neste trabalho introduzimos uma nova abordagem de classificação supervisionada, chamada Classifica-Normaliza-Classifica (CNC), para amenizar o problema de deslocamento dos dados. A proposta é implementada usando dois classificadores. O primeiro é treinado em imagens não normalizadas de refletância de topo de atmosfera para distinguir dentre pixels de uma classe de interesse (CDI) e pixels de outras categorias (e.g. floresta versus não-floresta). Dada uma nova imagem de teste, o primeiro classificador gera uma segmentação das regiões da CDI e então um vetor mediano é calculado para os valores espectrais dessas áreas. Então, esse vetor é subtraído de cada pixel da imagem e portanto fixa a distribuição de dados de diferentes imagens num mesmo referencial. Finalmente, o segundo classificador, que é treinado para minimizar o erro de classificação em imagens já centralizadas pela mediana, é aplicado na imagem de teste normalizada no segundo passo para produzir a segmentação binária final. A metodologia proposta foi testada para detectar desflorestamento em pares de imagens co-registradas da Landsat 8 OLI sobre a floresta Amazônica. Experimentos usando imagens multiespectrais de refletância de topo de atmosfera mostraram que a CNC obteve maior acurácia na detecção de desflorestamento do que classificadores aplicados em imagens de refletância de superfície fornecidas pelo United States Geological Survey. As acurácias do método proposto também se mostraram superiores às obtidas pelas máscaras de desflorestamento do programa PRODES. / Monitoring natural environments and their changes over time requires the analysis of a large amount of image data, often collected by orbital remote sensing platforms. However, variations in the observed signals due to changing atmospheric conditions often result in a data distribution shift for different dates and locations making it difficult to discriminate between various classes in a dataset built from several images. This work introduces a novel supervised classification framework, called Classify-Normalize-Classify (CNC), to alleviate this data shift issue. The proposed scheme uses a two classifier approach. The first classifier is trained on non-normalized top-of-the-atmosphere reflectance samples to discriminate between pixels belonging to a class of interest (COI) and pixels from other categories (e.g. forest vs. non-forest). At test time, the estimated COI’s multivariate median signal, derived from the first classifier segmentation, is subtracted from the image and thus anchoring the data distribution from different images to the same reference. Then, a second classifier, pre-trained to minimize the classification error on COI median centered samples, is applied to the median-normalized test image to produce the final binary segmentation. The proposed methodology was tested to detect deforestation using bitemporal Landsat 8 OLI images over the Amazon rainforest. Experiments using top-of-the-atmosphere multispectral reflectance images showed that the deforestation was mapped by the CNC framework more accurately as compared to running a single classifier on surface reflectance images provided by the United States Geological Survey (USGS). Accuracies from the proposed framework also compared favorably with the benchmark masks of the PRODES program.

Traditional antennas have a lot of limitations as their performance is usually fixed by their initial geometry. On the other hand, modern communication systems are getting way to complicated compared to their earlier counterparts. This necessitates some special types of smart or reconfigurable antennas, which can dynamically adapt to the requirements of the communication systems more effectively. Using conventional single functional antennas is therefore not an efficient approach in these sort of communication systems. Considering all these factors, in this thesis, a beam steerable reconfigurable antenna system is presented that can yield the radiation patterns of multiple antennas with a single structure, necessary for 5G communication. This antenna system occupies comparatively much smaller space and can provide highly directive gain at different directions. It is expected that- in near future, further improvements of this type of antenna system can be performed to pave the way for some additional necessary functions required in modern communication systems.

For landscapes dominated by agriculture, land cover plays an important role in the balance between anthropogenic and natural forces. Therefore, the objective of this thesis is to describe two different methodologies that have been implemented to create high-resolution land cover classifications in a dominant agricultural landscape. First, an object-based segmentation approach will be presented, which was applied to historic, high resolution, panchromatic aerial photography. Second, a traditional per-pixel technique was applied to multi-temporal, multispectral, high resolution aerial photography, in combination with light detection and ranging (LIDAR) and independent component analysis (ICA). A critical analysis of each approach will be discussed in detail, as well as the ability of each methodology to generate landscape metrics that can accurately characterize the quality of the landscape. This will be done through the comparison of various landscape metrics derived from the different classifications approaches, with a goal of enhancing the literature concerning how these metrics vary across methodologies and across scales. This is a familiar problem encountered when analyzing land cover datasets over time, which are often at different scales or generated using different methodologies. The diversity of remotely sensed imagery, including varying spatial resolutions, landscapes, and extents, as well as the wide range of spatial metrics that can be created, has generated concern about the integrity of these metrics when used to make inferences about landscape quality. Finally, inferences will be made about land cover and land cover change dynamics for the state of Iowa based on insight gained throughout the process.

Depuis l'invention du scanner, les détecteurs à intégration de charges sont largement employés pour les applications d'imagerie biomédicale utilisant des rayons X. Néanmoins, des alternatives existent. Les développements réalisés en instrumentation pour les expériences en physique des hautes énergies ont permis l'émergence d'une nouvelle technologie de détection directe à base de semiconducteur. Cette nouvelle technologie, appelée détecteur à pixels hybrides, fonctionne en mode comptage de photons et permet de sélectionner l'énergie minimum des photons comptés. Le groupe imXgam du CPPM développe le démonstrateur PIXSCAN, un tomodensitomètre à rayons X basé sur le détecteur à pixels hybrides XPAD. L'objectif de ce développement est d'évaluer l'impact de la technologie à pixels hybrides sur la qualité des images et sur la dose délivrée lors d'examens tomodensitométriques du petit animal. Suite à un premier prototype de détecteur à pixels hybrides XPAD1 démontrant la faisabilité du projet, un imageur complet XPAD2 a été conçu et intégré dans le démonstrateur PIXSCAN. Depuis, avec l'évolution de l'industrie de la microélectronique, des améliorations notables ont été envisageables. Pour réduire la taille des pixels et améliorer la précision en énergie des détecteurs, une troisième version XPAD3 a été développée et sera prochainement intégrée dans un démonstrateur PIXSCAN de deuxième génération. Dans ce projet, mon travail de thèse a porté sur une participation à la conception des électroniques de lecture des détecteurs, la caractérisation des circuits et des détecteurs à pixels hybrides ainsi que sur la définition d'une architecture d'autocalibration des pixels en énergie.