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Proceedings Paper

Efficient method of target recognition based on spectral correlation of wideband resonance effects
Author(s): Vincent Sabio; Rama Chellappa
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Paper Abstract

The potential for automatic target recognition (ATR) processing of foliage-penetrating (FOPEN) SAR imagery requires very high bandwidth occupancies for sufficient range resolution to be achieved for the ATR task. The Army Research Laboratory (ARL) ultra-wideband (UWB) FOPEN SAR--with greater than 95% bandwidth occupancy--provides a suitable testbed for evaluation of UWB ATR techniques. Target signatures in these data are characterized by two temporally distinct responses: an early-time (driven) response, and a late-time (resonant) response. We propose an ATR technique for UWB data based on recognition of targets by their resonant signatures. Current resonance-extraction techniques, such as the singularity-expansion method, hinge on contemporary adaptations of Prony's algorithm; this method, however, generally performs poorly in the presence of noise and is computationally intensive. We propose a form of resonance analysis by application of linear-transform methods, using both classical Fourier techniques and contemporary multiresolution approaches. Target- declaration confidences are established by the correlation of two sets of spectral coefficients--one set from the transformed image data, and the other from a synthetic target template. This permits a fast, efficient scheme for recognition of target resonance effects in UWB imagery. UWB images from the ARL UWB FOPEN SAR instrumentation system were analyzed with canonical targets (dipoles) of differing dimensions and orientation. Results are presented and summarized for each of the targets and transform methods employed in the analysis.

Paper Details

Date Published: 9 June 1994
PDF: 8 pages
Proc. SPIE 2230, Algorithms for Synthetic Aperture Radar Imagery, (9 June 1994); doi: 10.1117/12.177182
Show Author Affiliations
Vincent Sabio, Army Research Lab. (United States)
Rama Chellappa, Univ. of Maryland/College Park (United States)

Published in SPIE Proceedings Vol. 2230:
Algorithms for Synthetic Aperture Radar Imagery
Dominick A. Giglio, Editor(s)

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