No description available.

Oceanic microwave remote sensing provides the data necessary for the estimation of significant geophysical parameters such as the near-surface vector wind. To obtain accurate estimates, a precise understanding of the measurements is critical. This work clarifies and quantifies specific uncertainties in the scattered power measured by an active radar instrument. While there are many sources of uncertainty in remote sensing measurements, this work concentrates on three significant, yet largely unstudied effects. With a theoretical derivation of the backscatter from an ocean-like surface, results from this dissertation demonstrate that the backscatter decays with surface roughness with two distinct modes of behavior, affected by the size of the footprint. A technique is developed and scatterometer data analyzed to quantify the variability of spaceborne backscatter measurements for given wind conditions; the impact on wind retrieval is described in terms of bias and the Cramer-Rao lower bound. The probability density function of modified periodogram averages (a spectral estimation technique) is derived in generality and for the specific case of power estimates made by the NASA scatterometer. The impact on wind retrieval is quantified.

Because the earth's cryosphere influences global weather patterns and climate, the scientific community has had great interest in monitoring this important region. Microwave remote sensing has proven to be a useful tool in estimating sea and glacial ice surface characteristics with both scatterometers and radiometers exhibiting high sensitivity to important ice properties. This dissertation presents an array of studies focused on extracting key surface features from multisensor microwave data sets. First, several enhanced resolution image reconstruction issues are addressed. Among these are the optimization of the scatterometer image reconstruction (SIR) algorithm for NASA scatterometer (NSCAT) data, an analysis of Ku-band azimuthal modulation in Antarctica, and inter-sensor European Remote Sensing Satellite (ERS) calibration. Next, various methods for the removal of atmospheric distortions in image reconstruction of passive radiometer observations are considered. An automated algorithm is proposed which determines the spatial extent of sea ice in the Arctic and Antarctic regions from NSCAT data. A multisensor iterative sea ice statistical classification method which adapts to the temporally varying signatures of ice types is developed. The sea ice extent and classification algorithms are adopted for current SeaWinds scatterometer data sets. Finally, the automated inversion of large-scale forward electromagnetic scattering of models is considered and used to study the temporal evolution of the scattering properties of polar sea ice.

Radio tomographic imaging (RTI) is a novel device-free localization technique which utilizes the changes in radio signals caused by obstruction to enable various sensing applications. However, the deployment of these applications is hindered by the energy-expensive radio sensing techniques employed in these systems. In this thesis, we tackle this issue by introducing a novel way to realize a battery-free RTI sensor. We go through the design process and produce and evaluate a working prototype that operates on minuscule amounts of energy. Our design reduces power consumption by orders of magnitude compared to traditional RTI sensors by eliminating the energy-expensive components used in current RTI systems, enabling battery-free operation of RTI sensors. We demonstrate the efficiency and accuracy of our system in a boundary crossing scenario. We Discuss its limitations and tackle some of the security threats correlated with the deployment of such a system. / Radiotomografisk avbildning (RTA) är en ny, anordningsfri lokaliseringstekniksom utnyttjar förändringarna i radiosignaler orsakat av obstruktioner för att möjliggöraolika avkänningsapplikationer. Utvecklingen av dessa applikationer hindrasemellertid av de energiineffektiva radioavkännande tekniker som användsi dessa system. I denna avhandling behandlar vi problemet genom att introduceraen ny metod för att skapa en batterifri RTA-sensor. Vi går igenom konstruktionsprocessenoch producerar och utvärderar en arbetsprototyp som kräver minusklermängder energi. Vår design minskar energiförbrukningen signifikantjämfört med traditionella RTA-sensorer, genom att eliminera de energiineffektivakomponenterna som används i dagens RTA-system, vilket möjliggör batterifridrift av RTA-sensorer. Vi demonstrerar effektiviteten och noggrannheten hos vårtsystem i ett gränsöverskridande scenario. Vi diskuterar begränsningarna och taritu med några av de säkerhetshot som är korrelerade med utplaceringen av ettsådant system.

Electron Backscatter Diffraction (EBSD) is a well-developed technique used to perform quantitative microstructure analysis in the Scanning Electron Microscope (SEM); however, it has not been widely applied towards studying nanostructures. This work focuses on the use and limitations of EBSD in the characterization of Au nanoparticles on an MgAl2O4 substrate. Samples under investigation are prepared by depositing a thin film of Au on an MgAl2O4 substrate, and then finally heated in a furnace to induce dewetting and cluster formation. The challenges of obtaining crystallographic information from nanoparticles using EBSD are qualitatively and quantitatively described through an evaluation of the quality of the diffraction pattern at various locations of the primary electron beam on the nanoparticle. It is determined that for a high quality Electron Backscatter Diffraction Pattern (EBSP), the production of diffracted backscattered electrons travelling towards the detector must be high and the depth of the source point must be low. The top of the nanoparticle, where the local geometry of the system is similar to the geometry of a macroscopically flat sample, is found to produce diffraction patterns of the highest quality. On the other hand, reversed-contrast EBSPs are observed when the beam is positioned near the bottom of the nanoparticle. In addition, crystallographic information for each individual nanoparticle is gathered using EBSD. Each individual AuNP is observed to be single crystalline. Finally, the complete ensemble of crystalline orientations for individual nanoparticles is then compared to the global averaged crystallinity of the sample, as measured by X-ray diffraction. These results show that EBSD promises to be a powerful and robust technique in the characterization of nanoparticles. / Thesis / Master of Applied Science (MASc)

No description available.

No description available.

No description available.

The success of the Internet-of-Things (IoT) paradigm relies on, among other things, developing energy-efficient communication techniques that can enable information exchange among billions of battery-operated IoT devices. With its technological capability of simultaneous information and energy transfer, ambient backscatter is quickly emerging as an appealing solution for this communication paradigm, especially for the links with low data rate requirements. However, many challenges and limitations of ambient backscatter have to be overcome for widespread adoption of the technology in future wireless networks. Motivated by this, we study the design and implementation of ambient backscatter systems, including non-coherent detection and encoding schemes, and investigate techniques such as multiple antenna interference cancellation and frequency-shift backscatter to improve the bit error rate performance of the designed ambient backscatter systems. First, the problem of coherent and semi-coherent ambient backscatter is investigated by evaluating the exact bit error rate (BER) of the system. The test statistic used for the signal detection is based on the averaging of energy of the received signal samples. It is important to highlight that the conditional distributions of this test statistic are derived using the central limit theorem (CLT) approximation in the literature. The characterization of the exact conditional distributions of the test statistic as non-central chi-squared random variable for the binary hypothesis testing problem is first handled in our study, which is a key contribution of this particular work. The evaluation of the maximum likelihood (ML) detection threshold is also explored which is found to be intractable. To overcome this, alternate strategies to approximate the ML threshold are proposed. In addition, several insights for system design and implementation are provided both from analytical and numerical standpoints. Second, the highly appealing non-coherent signal detection is explored in the context of ambient backscatter for a time-selective channel. Modeling the time-selective fading as a first-order autoregressive (AR) process, we implement a new detection architecture at the receiver based on the direct averaging of the received signal samples, which departs significantly from the energy averaging-based receivers considered in the literature. For the proposed setup, we characterize the exact asymptotic BER for both single-antenna (SA) and multi-antenna (MA) receivers, and demonstrate the robustness of the new architecture to timing errors. Our results demonstrate that the direct-link (DL) interference from the ambient power source leads to a BER floor in the SA receiver, which the MA receiver can avoid by estimating the angle of arrival (AoA) of the DL. The analysis further quantifies the effect of improved angular resolution on the BER as a function of the number of receive antennas. Third, the advantages of utilizing Manchester encoding for the data transmission in the context of non-coherent ambient backscatter have been explored. Specifically, encoding is shown to simplify the detection procedure at the receiver since the optimal decision rule is found to be independent of the system parameters. Through extensive numerical results, it is further shown that a backscatter system with Manchester encoding can achieve a signal-to-noise ratio (SNR) gain compared to the commonly used uncoded direct on-off keying (OOK) modulation, when used in conjunction with a multi-antenna receiver employing the direct-link cancellation. Fourth, the BER performance of frequency-shift ambient backscatter, which achieves the self-interference mitigation by spatially separating the reflected backscatter signal from the impending source signal, is investigated. The performance of the system is evaluated for a non-coherent receiver under slow fading in two different network setups: 1) a single interfering link coming from the ambient transmission occurring in the shifted frequency region, and 2) a large-scale network with multiple interfering signals coming from the backscatter nodes and ambient source devices transmitting in the band of interest. Modeling the interfering devices as a two dimensional Poisson point process (PPP), tools from stochastic geometry are utilized to evaluate the bit error rate for the large-scale network setup. / Doctor of Philosophy / The emerging paradigm of Internet-of-Things (IoT) has the capability of radically transforming the human experience. At the heart of this technology are the smart edge devices that will monitor everyday physical processes, communicate regularly with the other nodes in the network chain, and automatically take appropriate actions when necessary. Naturally, many challenges need to be tackled in order to realize the true potential of this technology. Most relevant to this dissertation are the problems of powering potentially billions of such devices and enabling low-power communication among them. Ambient backscatter has emerged as a useful technology to handle the aforementioned challenges of the IoT networks due to its capability to support the simultaneous transfer of information and energy. This technology allows devices to harvest energy from the ambient signals in the environment thereby making them self-sustainable, and in addition provide carrier signals for information exchange. Using these attributes of ambient backscatter, the devices can operate at very low power which is an important feature when considering the reliability requirements of the IoT networks. That said, the ambient backscatter technology needs to overcome many challenges before its widespread adoption in IoT networks. For example, the range of backscatter is limited in comparison to the conventional communication systems due to self-interference from the power source at a receiver. In addition, the probability of detecting the data in error at the receiver, characterized by the bit error rate (BER) metric, in the presence of wireless multipath is generally poor in ambient backscatter due to double path loss and fading effects observed for the backscatter link. Inspired by this, the aim of this dissertation is to come up with new architecture designs for the transmitter and receiver devices that can improve the BER performance. The key contributions of the dissertation include the analytical derivations of BER which provide insights on the system design and the main parameters impacting the system performance. The exact design of the optimal detection technique for a communication system is dependent on the channel behavior, mainly the time-varying nature in the case of a flat fading channel. Depending on the mobility of devices and scatterers present in the wireless channel, it can either be described as time-selective or time-nonselective. In the time-nonselective channels, coherent detection that requires channel state information (CSI) estimation using pilot signals can be implemented for ambient backscatter. On the other hand, non-coherent detection is preferred when the channel is time-selective since the CSI estimation is not feasible in such scenarios. In the first part of this dissertation, we analyze the performance of ambient backscatter in a point-to-point single-link system for both time-nonselective and time-selective channels. In particular, we determine the BER performance of coherent and non-coherent detection techniques for ambient backscatter systems in this line of work. In addition, we investigate the possibility of improving the BER performance using multi-antenna and coding techniques. Our analyses demonstrate that the use of multi-antenna and coding can result in tremendous improvement of the performance and simplification of the detection procedure, respectively. In the second part of the dissertation, we study the performance of ambient backscatter in a large-scale network and compare it to that of the point-to-point single-link system. By leveraging tools from stochastic geometry, we analytically characterize the BER performance of ambient backscatter in a field of interfering devices modeled as a Poisson point process.

L’agrégation érythrocytaire est le principal facteur responsable des propriétés non newtoniennes sanguines pour des conditions d’écoulement à faible cisaillement. Lorsque les globules rouges s’agrègent, ils forment des rouleaux et des structures tridimensionnelles enchevêtrées qui font passer la viscosité sanguine de quelques mPa.s à une centaine de mPa.s. Cette organisation microstructurale érythrocytaire est maintenue par des liens inter-globulaires de faible énergie, lesquels sont brisés par une augmentation du cisaillement. Ces propriétés macroscopiques sont bien connues. Toutefois, les liens étiologiques entre ces propriétés rhéologiques générales et leurs effets pathophysiologiques demeurent difficiles à évaluer in vivo puisque les propriétés sanguines sont dynamiques et fortement tributaires des conditions d’écoulement. Ainsi, à partir de propriétés rhéologiques mesurées in vitro dans des conditions contrôlées, il devient difficile d’extrapoler leurs valeurs dans un environnement physiologique. Or, les thrombophlébites se développent systématiquement en des loci particuliers du système cardiovasculaire. D’autre part, plusieurs études cliniques ont établi que des conditions hémorhéologiques perturbées constituent des facteurs de risque de thrombose veineuse mais leurs contributions étiologiques demeurent hypothétiques ou corrélatives. En conséquence, un outil de caractérisation hémorhéologique applicable in vivo et in situ devrait permettre de mieux cerner et comprendre ces implications. Les ultrasons, qui se propagent dans les tissus biologiques, sont sensibles à l’agrégation érythrocytaire. De nature non invasive, l’imagerie ultrasonore permet de caractériser in vivo et in situ la microstructure sanguine dans des conditions d’écoulements physiologiques. Les signaux ultrasonores rétrodiffusés portent une information sur la microstructure sanguine reflétant directement les perturbations hémorhéologiques locales. Une cartographie in vivo de l’agrégation érythrocytaire, unique aux ultrasons, devrait permettre d’investiguer les implications étiologiques de l’hémorhéologie dans la maladie thrombotique vasculaire. Cette thèse complète une série de travaux effectués au Laboratoire de Biorhéologie et d’Ultrasonographie Médicale (LBUM) du centre de recherche du Centre hospitalier de l’Université de Montréal portant sur la rétrodiffusion ultrasonore érythrocytaire et menant à une application in vivo de la méthode. Elle se situe à la suite de travaux de modélisation qui ont mis en évidence la pertinence d’un modèle particulaire tenant compte de la densité des globules rouges, de la section de rétrodiffusion unitaire d’un globule et du facteur de structure. Ce modèle permet d’établir le lien entre la microstructure sanguine et le spectre fréquentiel du coefficient de rétrodiffusion ultrasonore. Une approximation au second ordre en fréquence du facteur de structure est proposée dans ces travaux pour décrire la microstructure sanguine. Cette approche est tout d’abord présentée et validée dans un champ d’écoulement cisaillé homogène. Une extension de la méthode en 2D permet ensuite la cartographie des propriétés structurelles sanguines en écoulement tubulaire par des images paramétriques qui mettent en évidence le caractère temporel de l’agrégation et la sensibilité ultrasonore à ces phénomènes. Une extrapolation menant à une relation entre la taille des agrégats érythrocytaires et la viscosité sanguine permet l’établissement de cartes de viscosité locales. Enfin, il est démontré, à l’aide d’un modèle animal, qu’une augmentation subite de l’agrégation érythrocytaire provoque la formation d’un thrombus veineux. Le niveau d’agrégation, la présence du thrombus et les variations du débit ont été caractérisés, dans cette étude, par imagerie ultrasonore. Nos résultats suggèrent que des paramètres hémorhéologiques, préférablement mesurés in vivo et in situ, devraient faire partie du profil de risque thrombotique. / The aggregation of erythrocytes is the main determinant of blood non Newtonian behaviour under low shearing flow conditions. When red blood cells (RBCs) aggregate, they form « rouleaux » and complex tridimensional structures that increase blood viscosity from a few mPa.s to a hundred mPa.s. The reversible RBC aggregation phenomenon is attributed to weak adhesive links between erythrocytes that are readily broken by increasing flow shearing. Blood bulk rheological properties have been comprehensively studied. However, the in vivo physiological impacts of abnormal clustering of RBCs are more difficult to assess. Clinical studies have identified altered hemorheology as a risk factor for thrombosis, but a clear etiological relationship between abnormal aggregation and thrombosis has not yet been established, in part because clinical conclusions were derived from correlative findings. It is to note that cardiovascular diseases such as deep venous thrombosis generally occur at specific locations within the vascular bed, suggesting a hemodynamic contribution to the development of this disease. Consequently, it is postulated that in vivo hemorheological characterization may help shed some light on the role of RBC hyper-aggregation on cardiovascular disorders. Ultrasound imaging, a non-invasive method relying on the propagation of mechanical waves within biological tissues, is sensitive to RBC aggregation. Indeed, the study of backscattered waves allows characterizing blood microstructure in vivo and in situ under physiological flow conditions. The work described in this thesis is based on prior simulation studies, performed at the Laboratory of Biorheology and Medical Ultrasonics of the University of Montreal Hospital Research Center, in which the backscattering of ultrasound from aggregating RBCs was modeled by considering a particle scattering strategy. In this approach, each RBC is a weak ultrasound scatterer (Born assumption) and the backscattering coefficient is modeled as the product of the RBC number density, the RBC backscattering cross section and a structure factor. This model relates variations in the backscattering coefficient to the RBC spatial organisation through the structure factor, which is the only parameter that changes during the aggregation process. A second order expansion in frequency of the structure factor was used to describe blood microstructure in terms of a packing factor W and an ensemble averaged aggregate diameter D. The model was first presented and validated by considering a homogenous shear flow condition using three broadband mono-element transducers. It was then extended in 2D to allow computation of parametric images in tube flow. An extrapolation based on the assumption that viscosity is related to the level of aggregation was used to compute local viscosity maps. Finally, a last contribution was the demonstration that a sudden increase in aggregation tendency directly promoted the formation of venous thrombosis in an experimental animal model. In that study, RBC aggregation, thrombus formation and flow variations were monitored longitudinally for two weeks using ultrasound. The results reported in this thesis suggest that rheological parameters on RBC clustering, ideally assessed in vivo and in situ, should be included in thrombosis risk profiling.