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Proceedings Paper

Method using multiple models to superresolve SAR imagery
Author(s): Frank M. Candocia; Jose C. Principe
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Paper Abstract

This paper introduces a methodology for the superresolution of synthetic aperture radar (SAR) images using multiple target and clutter models. The system has two major components: a mechanism that selects the appropriate model for superresolution and a bank of model estimators to accomplish the superresolution. The typical point scatterer model is incorporated into this technique as well as a model for clutter. Other models can be naturally incorporated. This methodology is flexible in that it can utilize many of the well-known modern spectral estimation techniques. The ability to more accurately model targets using models other than the point scatterer as well as the importance of including models for clutter into a superresolution paradigm is addressed. These issues are shown to be relevant to the automatic target recognition/detection problem. We present a comparison of our technique with other SAR imaging methods and discuss the relative benefits afforded by such an approach.

Paper Details

Date Published: 15 September 1998
PDF: 11 pages
Proc. SPIE 3370, Algorithms for Synthetic Aperture Radar Imagery V, (15 September 1998); doi: 10.1117/12.321824
Show Author Affiliations
Frank M. Candocia, Univ. of Florida (United States)
Jose C. Principe, Univ. of Florida (United States)


Published in SPIE Proceedings Vol. 3370:
Algorithms for Synthetic Aperture Radar Imagery V
Edmund G. Zelnio, Editor(s)

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