Super resolution for FOPEN SAR data

Hassan Shekarforoush; Amit Banerjee; Rama Chellappa

doi:10.1117/12.357151

27 July 1999 Super resolution for FOPEN SAR data

Hassan Shekarforoush, Amit Banerjee, Rama Chellappa

Proceedings Volume 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII; (1999) https://doi.org/10.1117/12.357151
Event: AeroSense '99, 1999, Orlando, FL, United States

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.

Citation Download Citation

Hassan Shekarforoush, Amit Banerjee, and Rama Chellappa "Super resolution for FOPEN SAR data", Proc. SPIE 3720, Signal Processing, Sensor Fusion, and Target Recognition VIII, (27 July 1999); https://doi.org/10.1117/12.357151

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available