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Proceedings Paper

Regularization based super resolution imaging using FFT:s
Author(s): Roland Jonsson
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Paper Abstract

This paper address the problem of super resolution imaging, using regularized amplitude estimation. Using a Bayesian problem formulation the regularization is applied through a prior distribution of the amplitudes. We investigate both a "super Gaussian" and a Student-t prior distribution. We derive maximum a posteriori (MAP) estimators for the amplitudes, based on the "Space-Alternating Generalized Expectation-Maximization" (SAGE) method, that only uses FFT:s in each iteration. The behavior of the algorithms for different choices of regularization parameters are illustrated through simple one dimensional examples, and SAR imaging is illustrated through an example using MSTAR data.

Paper Details

Date Published: 19 May 2005
PDF: 10 pages
Proc. SPIE 5808, Algorithms for Synthetic Aperture Radar Imagery XII, (19 May 2005); doi: 10.1117/12.604347
Show Author Affiliations
Roland Jonsson, Ericsson Microwave Systems AB (Sweden)

Published in SPIE Proceedings Vol. 5808:
Algorithms for Synthetic Aperture Radar Imagery XII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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