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Proceedings Paper

Adaptive high-definition imaging
Author(s): Gerald R. Benitz
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Paper Abstract

Adaptive high-definition imaging (HDI) is a data-adaptive approach to SAR image reconstruction based on superresolution techniques originally developed for passive sensor arrays. The problem at hand is the detection and recognition of ground-based targets in a clutter-dominated environment via UHF and L-Band foliage-penetrating SAR. Unfortunately, the resolution achieved in conventionally generated images is limited due to longer wavelengths and smaller bandwidths, as compared to high- resolution X- and Ka-Band SAR. A comparison of imaging techniques is presented, including conventional imaging, a 2D technique based on the MLM (Capon) algorithm, and a 2D version of the MUSIC algorithm. Results are presented for Wideband Rail SAR measurements of reflectors both in and out of foliage, demonstrating resolution improvement and clutter rejection. Also, results of processing data from an airborne wideband UHF SAR further demonstrate significant rejection of clutter which promises significant improvements in false-alarm performance.

Paper Details

Date Published: 9 June 1994
PDF: 14 pages
Proc. SPIE 2230, Algorithms for Synthetic Aperture Radar Imagery, (9 June 1994); doi: 10.1117/12.177195
Show Author Affiliations
Gerald R. Benitz, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 2230:
Algorithms for Synthetic Aperture Radar Imagery
Dominick A. Giglio, Editor(s)

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