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Proceedings Paper

Multiaperture ultrawideband SAR processing with polarimetric diversity
Author(s): Ravinder Kapoor; Nagaraj Nandhakumar
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Paper Abstract

We describe an approach for the interpretation of ultra-wideband (UWB) synthetic aperture radar (SAR) imagery for object classification. The UWB sensor is used for detection of manmade objects, including those which are obscured by a forest canopy. An electromagnetic model is used to predict the backscatter received from the scene objects. We show that the 'early-time' (physical optics) portion of the backscatter is highly dependent on the object structure. Hence, backscatter from scene objects that differ in structure, such as vehicles and trees, have different sensitivity to aspect angle of the incident wave. Manmade objects exhibit specular reflections ar certain aspect angles while natural objects generally do not. Aspect- angle sensitivity of the backscatter is extracted by reconstructing the SAR image of an object over smaller subapertures of the full synthetic aperture. This multi-aperture approach provides important angular information while still maintaining detectable levels in the subsequent SAR images. However, this information alone cannot be used to accurately classify objects due to a limited range of aspect angles and an inhomogeneous obscuring media. Consequently, this information is combined with polarization information to establish a robust feature vector for object classification. These features are shown to be useful in detecting vehicles obscured by foliage. Results of our approach on real data are presented.

Paper Details

Date Published: 5 June 1995
PDF: 12 pages
Proc. SPIE 2487, Algorithms for Synthetic Aperture Radar Imagery II, (5 June 1995); doi: 10.1117/12.210857
Show Author Affiliations
Ravinder Kapoor, Army Research Lab. (United States)
Nagaraj Nandhakumar, Univ. of Virginia (United States)

Published in SPIE Proceedings Vol. 2487:
Algorithms for Synthetic Aperture Radar Imagery II
Dominick A. Giglio, Editor(s)

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