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Proceedings Paper

Feature extraction algorithm for 3D scene modeling and visualization using monostatic SAR
Author(s): Julie Ann Jackson; Randolph L. Moses
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Paper Abstract

We present a feature extraction algorithm to detect scattering centers in three dimensions using monostatic synthetic aperture radar imagery. We develop attributed scattering center models that describe the radar response of canonical shapes. We employ these models to characterize a complex target geometry as a superposition of simpler, low-dimensional structures. Such a characterization provides a means for target visualization. Fitting an attributed scattering model to sensed radar data is comprised of two problems: detection and estimation. The detection problem is to find canonical targets in clutter. The estimation problem then fits the detected canonical shape model with parameters, such as size and orientation, that correspond to the measured target response. We present an algorithm to detect canonical scattering structures amidst clutter and to estimate the corresponding model parameters. We employ full-polarimetric imagery to accurately classify canonical shapes. Interformetric processing allows us to estimate scattering center locations in three-dimensions. We apply the algorithm to scattering prediction data of a simple scene comprised of canonical scatterers and to scattering predictions of a backhoe.

Paper Details

Date Published: 17 May 2006
PDF: 12 pages
Proc. SPIE 6237, Algorithms for Synthetic Aperture Radar Imagery XIII, 623708 (17 May 2006); doi: 10.1117/12.666558
Show Author Affiliations
Julie Ann Jackson, Ohio State Univ. (United States)
Randolph L. Moses, Ohio State Univ. (United States)


Published in SPIE Proceedings Vol. 6237:
Algorithms for Synthetic Aperture Radar Imagery XIII
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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