Paper
9 June 1994 Adaptive high-definition imaging
Gerald R. Benitz
Author Affiliations +
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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gerald R. Benitz "Adaptive high-definition imaging", Proc. SPIE 2230, Algorithms for Synthetic Aperture Radar Imagery, (9 June 1994); https://doi.org/10.1117/12.177195
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CITATIONS
Cited by 17 scholarly publications.
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KEYWORDS
Synthetic aperture radar

Reflectors

Scattering

Radar

Super resolution

Fourier transforms

Antennas

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