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Proceedings Paper

An algorithm for 3D target scatterer feature estimation from sparse SAR apertures
Author(s): Julie Ann Jackson; Randolph L. Moses
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Paper Abstract

We present an algorithm for extracting 3D canonical scattering features from complex targets observed over sparse 3D SAR apertures. The algorithm begins with complex phase history data and ends with a set of geometrical features describing the scene. The algorithm provides a pragmatic approach to initialization of a nonlinear feature estimation scheme, using regularization methods to deconvolve the point spread function and obtain sparse 3D images. Regions of high energy are detected in the sparse images, providing location initializations for scattering center estimates. A single canonical scattering feature, corresponding to a geometric shape primitive, is fit to each region via nonlinear optimization of fit error between the regularized data and parametric canonical scattering models. Results of the algorithm are presented using 3D scattering prediction data of a simple scene for both a densely-sampled and a sparsely-sampled SAR measurement aperture.

Paper Details

Date Published: 28 April 2009
PDF: 12 pages
Proc. SPIE 7337, Algorithms for Synthetic Aperture Radar Imagery XVI, 73370H (28 April 2009); doi: 10.1117/12.820497
Show Author Affiliations
Julie Ann Jackson, The Ohio State Univ. (United States)
Randolph L. Moses, The Ohio State Univ. (United States)

Published in SPIE Proceedings Vol. 7337:
Algorithms for Synthetic Aperture Radar Imagery XVI
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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