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Proceedings Paper

New approach to parametric HRR signature modeling for improved 1D ATR
Author(s): Bradley S. Denney; Rui J. P. de Figueiredo; Robert L. Williams
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Paper Abstract

Model-based HRR signature prediction and matching is a difficult problem due to target variations, lack of model fidelity, and sensor variations. For this reason, model-based HRR signatures often mismatch actual measured signatures. This paper introduces a novel method for predicting signatures by creating a Parametric HRR signature model from existing measured or model-based signatures. The method identifies potential three-dimensional persistent virtual scatterers and estimates their scattering patterns. The result is a parametric signature function of azimuth which better matches available signature data. The model effectively smoothes the signatures along the scatterer tracks. When used with synthetic data the technique helps eliminate model inaccuracies and uncertainties which manifest themselves in scatterer interference predictions. With sparse measured HRR profile observations, the parametric method smoothly interpolates profiles over azimuth. The parameterization method is aided by a Modified Inverse Radon Transform for persistent scatterer localization and a Fourier decomposition for scattering pattern approximation. Results using the predicted synthetic signatures in ATR multi-class problem are presented and compared with the performance based on the original synthetic and measured signatures. Results from these experiments show that this method provides a modest increase in ATR performance for synthetic signatures. The performance with sparse measured data is greatly improved and approaches dense measured data performance.

Paper Details

Date Published: 24 August 2000
PDF: 12 pages
Proc. SPIE 4053, Algorithms for Synthetic Aperture Radar Imagery VII, (24 August 2000); doi: 10.1117/12.396349
Show Author Affiliations
Bradley S. Denney, Neural Computing Systems (United States)
Rui J. P. de Figueiredo, Neural Computing Systems and Univ. of California/Irvine (United States)
Robert L. Williams, Air Force Research Lab. (United States)

Published in SPIE Proceedings Vol. 4053:
Algorithms for Synthetic Aperture Radar Imagery VII
Edmund G. Zelnio, Editor(s)

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