The series of experimental studies to be described has been carried out in order to determine the feasibility of using corner reflectors as laboratory standards for model cross-section measurements.

The rapid growth in the number of large wind farms has raised serious concerns about their effects on existing radar systems. The large size and rotational movement of the turbine blades can give rise to significant Doppler clutters, which interfere with the detection of moving targets such as aircraft and storms. A previous Air Force study has collected and analyzed the time-varying radar cross section resulting from the blade rotation of a single 1.5 MW turbine. However, multiple interactions taking place in a turbine were not studied in detail. Multiple interactions could play an important role in the propagation of radar signals through wind farms. This thesis sets out to more closely examine the various Doppler features resulting from the scattering due to a single turbine. Backscattered and forward scattered data are measured at Ku-band from various wind turbine models using a motorized turntable in the laboratory. The tested models include a 1:160 scale model turbine, a 3-arm wire model turbine, and a small wind turbine from Bergey Windpower with 2’ blades. The data are processed based on the short-time Fourier transform in order to relate the resulting time-varying Doppler features to various scattering mechanisms. The experimental findings are corroborated by simulations performed using the Numerical Electromagnetics Code (NEC). Furthermore, we propose a post-processing general method to reduce the intensity of the turbine scattered data. This method is applied to filter out simulated Doppler clutter from two different simulation techniques. First, the method is applied to remove the simulated Doppler clutter from the point scatterer model. Next, the algorithm is applied to simulated backscattered data generated using a high-frequency ray tracing code, Ahilo. / text

Sea ice is a vital component of the cryosphere and does not only influence the polar regions but has a more global influence. Indeed, sea ice plays a major role in the regulation of the global climate system as the sea ice cover reflects the sun radiation back to the atmosphere keeping the polar regions cool. The shrinkage of the sea ice cover entails the warming up of the oceans and as a consequence, a further amplification of the melting of sea ice. Therefore, the polar regions are sensitive to climate change and monitoring the sea ice cover is very important. To assess sea ice change in the polar regions, satellite active microwave sensors, scatterometers, are used to observe the evolution of sea ice extent and sea ice types. Thus, this research aims at creating a historic record of daily global Arctic and Antarctic sea ice extents and analysing the change in sea ice types with scatterometer data. A Bayesian sea ice detection algorithm, developed for the Advanced scatterometer (ASCAT), is applied and tuned to the configurations of the scatterometers on board the European Remote Sensing satellites, ERS\textendash 1 and ERS\textendash 2. The sea ice geophysical model functions (GMFs) of ERS and ASCAT are studied together to validate the use of ASCAT sea ice GMF extrapolated to the lower incidence angles of ERS. The main adaptations from the initial algorithm aim at compensating for the lower observation densities afforded by ERS with a refined spatial filter and time\textendash variable detection thresholds. To further analyse the backscatter response from sea ice and derive information on the different sea ice types, a new model of sea ice backscattering at C\textendash band is proposed in this study. This model has been derived using ERS and ASCAT backscatter data and describes the variation of sea ice backscatter with incidence angle as a function of sea ice type. The improvement of the sea ice detection algorithm for ERS\textendash 1 and ERS\textendash 2, operating between 1992 and 2001, leads to the extension of the existing records of daily global sea ice extents from the Quick scatterometer (QuikSCAT) which operated from 1999 to 2009 and ASCAT operating from 2007 onwards. The sea ice extents from ERS, QuikSCAT and ASCAT show excellent agreement during the overlapping periods, attesting to the consistency and homogeneity of the long\textendash term scatterometer sea ice record. The new climate record is compared against passive microwave derived sea ice extents, revealing consistent differences between spring and summer which are attributed to the lower sensitivity of the passive microwave technique to melting sea ice. The climate record shows that the minimum Arctic summer sea ice extent has been declining, reaching the lowest record of sea ice extent in 2012. The new model for sea ice backscatter is used on ERS and ASCAT backscatter data and provides a more precise normalization of sea ice backscatter than was previously available. An application of this model in sea ice change analysis is performed by classifying sea ice types based on their normalized backscatter values. This analysis reveals that the extent of multi\textendash year Arctic sea ice has been declining remarkably over the period covered by scatterometer observations.

abstract: A domain decomposition method for analyzing very large FDTD domains, hundreds of thousands of wavelengths long, is demonstrated by application to the problem of radar scattering in the maritime environment. Success depends on the elimination of artificial scattering from the “sky” boundary and is ensured by an ultra-high-performance absorbing termination which eliminates this reflection at angles of incidence as shallow as 0.03 degrees off grazing. The two-dimensional (2D) problem is used to detail the features of the method. The results are cross-validated by comparison to a parabolic equation (PE) method and surface integral equation method on a 1.7km sea surface problem, and to a PE method on propagation through an inhomogeneous atmosphere in a 4km-long space, both at X-band. Additional comparisons are made against boundary integral equation and PE methods from the literature in a 3.6km space containing an inhomogeneous atmosphere above a flat sea at S-band. The applicability of the method to the three-dimensional (3D) problem is shown via comparison of a 2D solution to the 3D solution of a corridor of sea. As a technical proof of the scalability of the problem with computational power, a 5m-wide, 2m-tall, 1050m-long 3D corridor containing 321.8 billion FDTD cells has been simulated at X-band. A plane wave spectrum analysis of the (X-band) scattered fields produced by a 5m-wide, 225m-long realistic 3D sea surface, and the 2D analog surface obtained by extruding a 2D sea along the width of the corridor, reveals the existence of out-of-plane 3D phenomena missed by the traditional 2D analysis. The realistic sea introduces random strong flashes and nulls in addition to a significant amount of cross-polarized field. Spatial integration using a dispersion-corrected Green function is used to reconstruct the scattered fields outside of the computational FDTD space which would impinge on a 3D target at the end of the corridor. The proposed final approach is a hybrid method where 2D FDTD carries the signal for the first tens of kilometers and the last kilometer is analyzed in 3D. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2018

Les instruments, satellites ou systèmes aéroportés, actuellement utilisés pour la détection et la caractérisation d'hydrocarbure sur la mer sont basés sur des moyens optiques ou radars. Ces moyens présentent une performance dégradée due à une fréquence encore trop importante de fausses alarmes ou à un temps de traitement des données trop conséquent. Les méthodes de détection, d'identification et de quantification des fuites d'hydrocarbures offshores peuvent donc être améliorées en associant robustesse et réactivité. Cette amélioration suppose une compréhension approfondie des phénomènes océanographiques et électromagnétiques à l'œuvre dans cette scène particulière. La thèse s'appuie sur des données regroupant des images optiques et SAR aéroportées ou satellites ainsi que des mesures réalisées en laboratoire. Ce jeu de données permet de vérifier la cohérence des résultats obtenus par modélisation. L'objectif de la thèse est de distinguer une surface de mer polluée d'une surface de mer propre à l'aide de la signature électromagnétique de la surface totale puis de détailler le type et la quantité d'hydrocarbure présent. La thèse se divise en deux domaines, à savoir modélisation océanographique et modélisation électromagnétique. La modélisation océanographique intègre la simulation de la surface rugueuse imitant une surface de mer propre, et polluée. Cette surface de mer doit être générée sur une superficie importante et doit conserver une résolution restituant les petites vagues avec un temps de génération minimal. La partie électromagnétique est centrée sur les modèles asymptotiques de diffusion des ondes électromagnétiques par une interface rugueuse. Ces modèles sont adaptés au contexte de la thèse, complexité de la scène et rapidité du traitement, mais nécessitent plusieurs hypothèses pour être appliqués. / Satellites or airborne systems currently used for the detection and characterization of oil slicks on sea surface are based on optical or radar means. These means have a lack of performance due to a too high frequency of false alarms or to an excessively long data processing time. The methods for detecting, identifying and quantifying offshore pollutant can therefore be improved by combining robustness and reactivity. This improvement implies an in-depth understanding of the oceanographic and electromagnetic phenomena at work in this particular scene. The thesis is based on data gathering aerial and satellite images and SAR as well as measurements carried out in laboratory. This dataset makes it possible to check the consistency of the results obtained by modeling. The objective of the thesis is to distinguish a polluted sea surface from a clean sea surface using the electromagnetic signature of the total surface and then to detail the type and quantity of pollutant. The thesis is divided into two domains, namely oceanographic modeling and electromagnetic modeling. Oceanographic modeling integrates the simulation of the rough surface imitating a clean or polluted sea surface. This sea surface must be generated over a large area with a thin resolution. The electromagnetic part is centered on the asymptotic models for the electromagnetic waves diffraction by a rough interface. These models are adapted to the context of the thesis, the complexity of the scene and the speed of processing, but require several hypotheses to be applied.