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Proceedings Paper

Super resolution for FOPEN SAR data
Author(s): Hassan Shekarforoush; Amit Banerjee; Rama Chellappa
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Paper Abstract

Detecting targets occluded by foliage in Foliage penetrating (FOPEN) Ultra-Wide-Band Synthetic Aperture Radar (UWB SAR) images is an important and challenging problem. Given the different nature of FOPEN SAR imagery and very low signal- to-clutter ratio in UWB SAR data, conventional detection algorithms usually fail to yield robust target detection results on raw data with minimum false alarms. Hence improving the resolving power by means of a super-resolution algorithm plays an important role in hypothesis testing for false alarm mitigation and target localization. In this paper we present a new single-frame super-resolution algorithm based on estimating the polyphase components of the observed signal projected on an optimal basis. The estimated polyphase components are then combined into a single super-resolved image using the standard inverse polyphase transform, leading to improved target signature while suppressing noise.

Paper Details

Date Published: 27 July 1999
PDF: 7 pages
Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); doi: 10.1117/12.357151
Show Author Affiliations
Hassan Shekarforoush, Univ. of Maryland/College Park (United States)
Amit Banerjee, Univ. of Maryland/College Park (United States)
Rama Chellappa, Univ. of Maryland/College Park (United States)


Published in SPIE Proceedings Vol. 3720:
Signal Processing, Sensor Fusion, and Target Recognition VIII
Ivan Kadar, Editor(s)

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