Synthetic Aperture Radar Multi Polarization Ocean Characteristics And Ship Detection
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Synthetic Aperture Radar Multi-Polarization Ocean Characteristics and Ship Detection
Ce travail de thèse a été consacré à la caractérisation de la surface de la mer par radar à synthèse d'ouverture (RSO) polarimétrique porté par un satellite. Un modèle pour différents mécanismes de diffusion est mise en oeuvre, pour une meilleure compréhension de la contribution scalaire sur toutes les surface équivalentes radar (SER) et les mesures doppler par images RSO sur la mer. Généralement, il y a trois types des mécanismes de diffusion sur la surface quand la mer a été illuminée par une radar micro-onde, i.e., Bragg, spéculaire, et Rayleigh. La contribution de Bragg dépolarisée correspond à des petites vagues de capillarité-gravité, alors que les autres, contributions scalaires correspondent à la réflexion spéculaire par la crête des vagues qui est instable et déferle et la diffusion de Rayleigh sur la mousse après la vague déferlante. Différents mécanismes de diffusion impliquent des coefficients de diffusion polarimétrique différents et des spectres Doppler différents. Dans chaque pixel, la matrice de diffusion est modelisée physiquement en contributions Bragg et scalaire. La solution est une itération qui est initiée avec l'angle d'incidence, et est contrôlée par l'angle d'incidence local. Les estimateurs des matrices de diffusion Bragg et scalaire bénéficient d'un modèle statistique du fouillis de mer. Enfin, l'amélioration du modèle statistique avec la théorie de la détection est proposée au regard de la classification pour des cibles artificielles, comme les navires ou les plate-formes pétrolières.
Polarimetric Synthetic Aperture Radar
This open access book focuses on the practical application of electromagnetic polarimetry principles in Earth remote sensing with an educational purpose. In the last decade, the operations from fully polarimetric synthetic aperture radar such as the Japanese ALOS/PalSAR, the Canadian Radarsat-2 and the German TerraSAR-X and their easy data access for scientific use have developed further the research and data applications at L,C and X band. As a consequence, the wider distribution of polarimetric data sets across the remote sensing community boosted activity and development in polarimetric SAR applications, also in view of future missions. Numerous experiments with real data from spaceborne platforms are shown, with the aim of giving an up-to-date and complete treatment of the unique benefits of fully polarimetric synthetic aperture radar data in five different domains: forest, agriculture, cryosphere, urban and oceans.
Synthetic Aperture Radar (SAR) Data Applications
This carefully curated volume presents an in-depth, state-of-the-art discussion on many applications of Synthetic Aperture Radar (SAR). Integrating interdisciplinary sciences, the book features novel ideas, quantitative methods, and research results, promising to advance computational practices and technologies within the academic and industrial communities. SAR applications employ diverse and often complex computational methods rooted in machine learning, estimation, statistical learning, inversion models, and empirical models. Current and emerging applications of SAR data for earth observation, object detection and recognition, change detection, navigation, and interference mitigation are highlighted. Cutting edge methods, with particular emphasis on machine learning, are included. Contemporary deep learning models in object detection and recognition in SAR imagery with corresponding feature extraction and training schemes are considered. State-of-the-art neural network architectures in SAR-aided navigation are compared and discussed further. Advanced empirical and machine learning models in retrieving land and ocean information — wind, wave, soil conditions, among others, are also included.