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Proceedings Paper

Some results from scattering-based tomography for HRR and SAR prediction
Author(s): Bradley S. Denney; Katia Estabridis; Rui J. P. de Figueiredo; Keith J. Dillon
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Paper Abstract

The problem of predicting HRR radar and SAR signal magnitudes based on a limited number of observations is a challenging component of feature aided tracking. In this paper we describe the application of a scattering-based tomographic technique that builds persistent scatterer models of ground vehicles from a collection of HRR and/or SAR observations from varying look angles. Results are obtained using MSTAR data. Target detection results are shown using ROC curves and compared with nearest observation matching. Application of these techniques to the move-stop-move problem of vehicle tracking is also described.

Paper Details

Date Published: 12 September 2003
PDF: 12 pages
Proc. SPIE 5095, Algorithms for Synthetic Aperture Radar Imagery X, (12 September 2003); doi: 10.1117/12.487497
Show Author Affiliations
Bradley S. Denney, Neural Computing Systems (United States)
Katia Estabridis, Neural Computing Systems (United States)
Rui J. P. de Figueiredo, Neural Computing Systems (United States)
Keith J. Dillon, Neural Computing Systems (United States)


Published in SPIE Proceedings Vol. 5095:
Algorithms for Synthetic Aperture Radar Imagery X
Edmund G. Zelnio; Frederick D. Garber, Editor(s)

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