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Synthetic Aperture Radar Image Formation Via Sparse Decomposition


Abstract Spotlight mode synthetic aperture radar (SAR) imaging involves a tomo- graphic reconstruction from projections, necessitating acquisition of large amounts of data in order to form a moderately sized image. Since typical SAR sensors are hosted on mobile platforms, it is common to have limitations on SAR data acquisi- tion, storage and communication that can lead to data corruption and a resulting degradation of image quality. It is convenient to consider corrupted samples as missing, creating a sparsely sampled aperture. A sparse aperture would also result from compressive sensing, which is a very attractive concept for data intensive sen- sors such as SAR. Recent developments in sparse decomposition algorithms can be applied to the problem ... (more)
Created Date 2011
Contributor Werth, Nicholas (Author) / Karam, Lina (Advisor) / Papandreou-Suppappola, Antonia (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Subject Electrical Engineering / Image Segmentation / Matching Pursuit / Reweighted Least-Squares / SAR / Sparse Decomposition / Super-Resolution
Type Masters Thesis
Extent 115 pages
Language English
Copyright
Reuse Permissions All Rights Reserved
Note M.S. Electrical Engineering 2011
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis