The Phase Gradient Autofocus (PGA) algorithm is widely used in spotlight mode SAR for motion compensation. The Maximum Likelihood PGA (ML PGA) algorithm has been shown to be a superior autofocus method. The PGA is restricted to high altitude aircraft. Since lower altitude SARs have significant range dependencies that cannot be ignored, the PGA could not be used. This thesis eliminates the high altitude restriction and extends the PGA for use with all spotlight SARs. The new algorithm is tested with three images. Each image has a unique quality. A desert image provides a low signal to clutter ratio with no distinct targets and the mountain image has areas with high signal-to-clutter and areas with low signal-to-clutter. Each image was corrupted with a low frequency and high frequency motion induced low altitude phase error. The new Phase Weighted Estimation (PWE) low altitude autofocus method converged to a lower standard deviation than the ML PGA, but required more iterations. Another limitation of the PGA is that it will only work for spotlight SAR. In this thesis, the spotlight PGA is extended to stripmap by using a conversion similar to spotlight mode. With the space frequency relationship an altered PGA is used to extend the PGA to stripmap mode SAR. The stripmap SAR, range dependant PGA allows for focusing of low altitude low cost stripmap SARs. The phase weighted estimation method is extended to range dependent stripmap. The stripmap mode estimator is most successful with high signal-to-noise images.

Interferometry and coherent change detection (CCD) utilize phase differences between complex SAR images to find terrain height and to detect small changes between images, respectively. A new method for improving interferometry and CCD using multiple sub-apertures is proposed. Using backprojection processing, multiple sub-aperture images are created for a pair of flights. An interferogram and coherence map is made from each sub-aperture. For CCD, each sub-aperture coherence map offers an independent estimate of the coherence over the same area. By combining coherence maps, low coherence areas associated with residual motion errors are reduced, shadowed areas are minimized, and the overall coherence of stationary objects between images is increased. For interferometry, combining independent estimates of a scene's height offers a more accurate height estimate. For repeat-pass interferometry, multiple apertures are shown to increase the coverage of valid height estimates. The benefits of multi-aperture interferometry and CCD are shown using examples with real data.

This work presents the development and analysis of a system that combines the concepts of light field microscopy and particle image velocimetry (PIV) to measure three-dimensional velocities within a microvolume. Rectanglar microchannels were fabricated with dimensions on the order of 350-950 micrometers using a photolithographic process and polydimethylsiloxane (PDMS). The flow was seeded with fluorescent particles and pumped through microchannels at Reynolds numbers ranging from 0.016 to 0.028. Flow at Reynolds numbers in the range of 0.02 to 0.03 was seeded with fluorescent particles and pumped through microchannels. A light field microscope with a lateral resolution of 6.25 micrometers and an axial resolution of 15.5 micrometers was designed and built based on the concepts described by Levoy et al. Light field images were captured continuously at a frame rate of 3.9 frames per second using a Canon 5D Mark II DSLR camera. Each image was post processed to render a stack of two-dimensional images. The focal stacks were further post processed using various methods including bandpass filtering, 3D deconvolution, and intensity-based thresholding, to remove effects of diffraction and blurring. Subsequently, a multi-pass, three-dimensional PIV algorithm was used to measure channel velocities. Results from PIV analysis were compared with an analytical solution for fully-developed cases, and with CFD simulations for developing flows. Relative errors for fully-developed flow measurements, within the light field microscope refocusing range, were approximately 5% or less. Overall, the main limitations are the reduction in lateral resolution, and the somewhat low axial resolution. Advantages include the relatively low cost, ease of incorporation into existing micro-PIV systems, simple self-calibration process, and potential for resolving instantaneous three-dimensional velocities in a microvolume.

[pt] A captura de cenas de cobertura da Terra com sensores óticos de satélite é frequentemente limitada pela presença de nuvens que corrompem as imagens coletadas. Entre os métodos para recuperar imagens óticas de satélite corrompidas por nuvens, várias abordagens de tradução de imagemimagem usando Redes Adversárias Generativas (GANs) têm surgido com bons resultados, conseguindo criar imagens óticas realistas a partir de imagens de Radar de Abertura Sintética (SAR). Os métodos baseados em GANs condicionais (cGAN) propostos até agora para a síntese de imagens SAR-óticas tendem a produzir imagens ruidosas e com pouca nitidez. Neste trabalho, propomos a atrous-cGAN, uma nova arquitetura que melhora a transformação de imagem SAR em ótica. As redes propostas para o gerador e discriminador contam com convolusões dilatadas (atrous) e incorporam o módulo Pirâmide Espacial Atrous Pooling (ASPP) para realçar detalhes finos na imagem ótica gerada, explorando o contexto espacial em várias escalas. Este trabalho apresenta experimentos realizados para avaliar o desempenho da atrous-cGAN na síntese de imagens Landsat a partir de dados Sentinel-1A, usando quatro bases de dados públicas. A análise experimental indicou que a atrous-cGAN supera o modelo clássico pix2pix como uma ferramenta de aprendizado de atributos para segmentação semântica. A proposta também gera imagens com maior qualidade visual, e em geral com maior semelhança com a verdadeira imagem ótica. / [en] The capture of land cover scenes with optical satellite sensors is often constrained by the presence of clouds that corrupt the collected images. Among the methods for recovering satellite optical images corrupted by clouds, several image to image translation approaches using Generative Adversarial Networks (GANs) have emerged with profitable results, managing to create realistic optical images from Synthetic Aperture Radar (SAR) data. Conditional GAN (cGAN) based methods proposed so far for SAR-to-optical image synthesis tend to produce noisy and unsharp optical outcomes. In this work, we propose the atrous-cGAN, a novel cGAN architecture that improves the SAR-to-optical image translation. The proposed generator and discriminator networks rely on atrous convolutions and incorporate the Atrous Spatial Pyramid Pooling (ASPP) module to enhance fine details in the generated optical image by exploiting spatial context at multiple scales. This work reports experiments carried out to assess the performance of atrouscGAN for the synthesis of Landsat images from Sentinel-1A data based on four public datasets. The experimental analysis indicated that the atrouscGAN overcomes the classical pix2pix model as a feature learning tool for semantic segmentation. The proposal also generates higher visual quality images, in general with higher similarity with the true optical image.

В работе актуализируется цель создания учебного программного приложения, позволяющего моделировать процесс формирования и обработки сигналов в космических РСА высокого разрешения. В ходе работы разработано программное приложение, которое позволяет создать облучаемую сцену земной поверхности и сформировать в зависимости от сцены отраженный сигнал с пользовательскими характеристиками РСА, провести его обработку с целью получения радиоголограмм и радиолокационных изображений. Результатом разработки стало учебное программное приложение, которое позволит магистрам направления «Радиотехника» понять принцип формирования и обработки сигналов в космических РСА высокого разрешения и провести ряд исследований, направленных на изучения особенностей формирования радиолокационных изображений. / Problem of development of educational software application that allows to simulate the process of forming and signal processing in space high-resolution SAR is disclosed. In result software application that allows to create an irradiated scene of earth's surface and to form depending on the scene reflected signal with custom features SAR in order to obtain RF holograms and radar images was developed. The achievement is the educational software application that allows magisters of speciality «Radiotechnics» to understand the principle of formation and signal processing in high-resolution SAR and to perform a series of test aimed at studying the characteristics of radar image .

Microwave imaging finds numerous applications involving optically obscured targets. One particular area is breast cancer detection, since microwave technology promises fast low-cost image reconstruction without the use of harmful radiation typical of X-ray mammography. However, the success of microwave imaging is hindered by a critical issue, the complex nature of near-field electromagnetic scattering in tissue. To overcome this, specialized image reconstruction algorithms alongside sensitive measurement hardware are required. In this work, real-time near-field microwave imaging algorithms known as quantitative microwave holography and scattered power mapping are explored. They are experimentally demonstrated to identify potential tumor regions in tissue phantoms. Alongside this development, quality control techniques for evaluating microwave hardware are also described. Two new methods for improving the image reconstruction quality are also presented. First, a novel technique, which combines two commonly used mathematical approximations of scattering (the Born and Rytov approximations), is demonstrated yielding improved image reconstructions due to the complimentary nature of the approximations. Second, a range migration algorithm is introduced which enables near-field refocusing of a point-spread function (PSF), which is critical for algorithms that rely on measured PSFs to perform image reconstruction. / Thesis / Doctor of Philosophy (PhD) / Breast cancer remains as one of the highest causes of cancer-related deaths in women in Canada. Though X-ray mammography remains the gold standard for regular breast cancer screening, its use of harmful radiation, painful breast compression, and radiologist dependent evaluation remain as detracting factors for its use. Over the past 40 years, researchers have been exploring the use of microwave technology in place of X-ray mammography. Microwave radiation, used at power levels similar to that of a cellphone, has been demonstrated successfully in simulations of breast scans. However, in experimental evaluations with breast phantoms, the complex scattering path of the radiation through tissue complicates image reconstruction. In this thesis, methods of improving the accuracy of microwave algorithms are explored, alongside new breast phantom structures that replicate well the electrical properties of tissue. The results of this work demonstrate the flexibility of microwave imaging, and the adversities that still need to be overcome for it to begin seeing clinical use.

No description available.

Floods are the most frequent disaster in the world and flood exposure is increasing globally. Flood mapping of past events can be a useful aid in not only disaster risk management, but also in evaluating and validating global flood models (GFMs) which are being used to assess and predict these floods. There are however numerous ways of mapping floods, and it is uncertain how well these perform as validation data. In this paper, a change detection approach based on a combination of synthetic aperture radar (SAR) and cloud-computing to map past flood events is evaluated (hereinafter CD- SAR). Eight flood events were chosen over a wide range of hydroclimatic conditions, regions, and flood types. These eight events were mapped with CD-SAR and compared to four GFM outputs and two flood maps of past events from two commonly used databases. The spatial agreement between CD-SAR and the GFMs showed a considerable variation between regions and models. The agreement was however shown to share a similar interval to previous validation studies, albeit in the lower portion. CD-SAR also showed similar performance to the comparison between the GFMs and the outputs from the databases of mapped past flood events. The results were also analysed for how the flood extent and flood-edge distribution of CD-SAR compare to both the GFMs and the database outputs. The results showed a similar variation in distribution as the spatial agreement but did not follow the same trend for all regions. The flexibility and high resolution of CD-SAR allow it to cover events over a wider range of regions and of any size and it can be a viable tool to map past flood events and could be used to evaluate GFMs. However, CD-SAR needs further evaluation as uncertainties still exist due to the inherent characteristics of SAR and the revisit times of the satellites using SAR. / Översvämningsrelaterade katastrofer är de mest förekommande i världen och exponeringen för översvämningar ökar globalt. Kartläggningar av tidigare översvämningshändelser kan vara ett användbart verktyg för katastrofriskhantering samt för att utvärdera och validera globala översvämningsmodeller som används för att uppskatta och förutse översvämningar. Det finns ett flertal sätt att kartlägga översvämningar men det är osäkert hur bra de fungerar som valideringsdata. Denna studie utvärderar en metod för att kartlägga översvämningar genom förändringsdetektering i syntetiska aperturradarbilder (SAR) med hjälp av molntjänster (härefter CD-SAR). Åtta översvämningshändelser valdes över en rad hydroklimatiska förhållanden, regioner och översvämningstyper. De här översvämningshändelserna kartlades med hjälp av CD-SAR och jämfördes med fyra globala översvämningsmodeller och två översvämningskartor från två väl använda databaser. CD-SAR och de fyra globala översvämningsmodellerna visade betydliga skillnader i överenstämmelse mellan både regioner och modeller. Överenstämmelsen var dock inom samma intervall som påvisats i tidigare studier om än något lägre. CD-SAR visade sig också ha en liknande överensstämmelse som jämförelsen mellan modellerna och databaserna. En analys av CD- SAR jämfört med modellerna och databaserna genomfördes över utbredningen av översvämningarna och dess fördelningar. Resultaten visade en liknande variation som överenstämmelsen men följde inte samma trender för alla regioner. CD-SAR:s flexibilitet och dess höga upplösning gör att den kan omfatta ett stort antal översvämningshändelser över en rad olika regioner. Det gör det möjligt för CD- SAR att genomföra översvämningskartläggningar och för att utvärdera globala översvämningsmodeller. CD-SAR behöver dock utvärderas ytterligare då metoden fortfarande innehar vissa osäkerheter. Osäkerheterna är till mestadels på grund av de inneboende egenskaperna hos SAR samt täckningen för satelliterna som använder SAR.

<p>Basic radar systems use electromagnetic wave reflections from targets to determine the motion characteristics of these targets. Synthetic Aperture Radar (SAR) systems use the reflections to produce target images as well. SAR is an imaging radar system that produces high resolution images of a scene or target by using radar motion to synthesize the antenna aperture. A SAR model to handle extended targets and point targets in faster time is presented, as are some simulated results. This thesis explains synthetic aperture concepts, the model used and a simulation of a SAR system. It runs through modelling point targets as well as extended targets by using the resolution cells of the radar, creating the raw signal data from the target information and then the signal processing that converts the raw data to a SAR image. The simulation was done for better understanding of synthetic aperture parameters and it was done in C++ programming language for improved processing speed. In comparison to previous simulations obtained from literature review, there is an increase in speed of more than 2.5 times as the number of targets increases, producing higher resolution images in less time. A model to handle extended targets was presented while also showing the imperfections due to the model assumptions. These assumptions are then explained as the best option in the absence of extra geographic information on the target scene.</p> / Master of Applied Science (MASc)

Throughout the years of space exploration, the usage of Earth observation satellites has increased tremendously. The usage today extends beyond optical sensors, encompassing radars, infrared, and laser sensors. For this thesis, the usage of optical, synthetic aperture radar, and LiDAR sensors were looked at to see if the fusion of these different sensors could enhance the overall image quality. A crucial aspect of satellite image fusion, regardless of sensor type, is preprocessing to ensure the individual images can be seamlessly merged. Ultimately these preprocessing steps are individual to both the sensors and even different satellites. The topic of remote sensing and satellite image fusion is extensive and complex. Therefore, this thesis aims to explore various fusion techniques, data sources, and algorithms to contribute to a deeper understanding of the advantages but mostly challenges associated with multisensor satellite image fusion. A web scraper was developed to collect data from the European Space Agency’s Third Party Mission website, a central repository for satellite missions and Earth images. The scraper made it possible to select different satellites and find the image areas which they had in common. A way to process this data is then presented on how to process the images and finally fuse them. The three fusion algorithms that were used were a simple weighted average, intensity hue saturation, and the pansharpening method. The pansharpening increased both the spatial and spectral resolution whereas the fusion of the optical and synthetic aperture radar gave some mixed results. There are a lot of things that could be explored in the future, such as utilizing more complex fusion algorithms or using additional satellite sensors. However, the web scraper and the processing flowchart stand as notable achievements of this thesis, simplifying the entire process of multisensor satellite image fusion. / Genom åren har användningen av jordobservationsatelliter ökat avsevärt inom rymdforskning. Användningen sträcker sig idag bortom optiska sensorer och inkluderar även radar-, infraröd- och lasersensorer. I detta examensarbete undersöks användningen av optiska, syntetisk aperturradar- och LiDARsensorer för att se om fusionen av dessa olika sensorer kan förbättra helhetsbilden av ett område. En avgörande aspekt av satellitbildsfusion, oavsett sensortyp, är förbehandling för att säkerställa att de individuella bilderna kan smidigt integreras. Slutligen är dessa förbehandlingsteg specifika för både sensorerna och olika satelliter. Ämnet fjärranalys och fusion av satellitbilder är omfattande och komplext. Därför syftar detta examensarbete till att utforska olika fusionsmetoder, datakällor och algoritmer för att bidra till en djupare förståelse för fördelarna och utmaningarna med multisensor fusion av satellitbilder. Ett av huvudproblemen under examensarbetet var datainsamling och databehandling. För att överkomma detta utvecklades en webbskrapare för att samla in data från European Space Agencys Third Party Mission hemsida, en central databas för satellituppdrag och bilder av jorden. Skrapan möjliggjorde valet av olika satelliter och identifieringen av gemensamma bildområden. En metod för databehandling presenteras sedan för att bearbeta bilderna och slutligen förena dem. De tre fusionsalgoritmerna som användes var en enkel viktad medelvärdesmetod, intensitetssättning och pansharpening. Pansharpening ökade både den spatiala och spektrala upplösningen, medan fusionen av optiska och syntetisk aperturradar gav blandade resultat. Det finns många områden som kan utforskas i framtiden, såsom användning av mer komplexa fusionsalgoritmer eller ytterligare satellitsensorer. Sammanfattande kan webbskrapan och behandlingsflödet ses som betydande framsteg i detta examensarbete och förhoppningsvis förenkla hela processen med multisensor fusion av satellitbilder.