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Proceedings Paper

Spectral correlation of wideband target resonances
Author(s): Vincent Sabio
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Paper Abstract

The US Army Research Laboratory (ARL), working with the University of Maryland Department of Electrical Engineering, recently developed a novel method for efficient recognition of resonances in imagery from ARL's ultra-wideband (UWB) SAR instrumentation system, currently being used in foliage- and ground-penetration studies. The recognition technique uses linear transforms (Fourier, wavelets, etc.) to provide a basis for the design of spectrally matched filters. Implementation of the technique is very straightforward: an expectation of the target ringdown is projected onto a transform basis set, yielding a set of spectral coefficients (the 'spectral template'). UWB SAR image data are projected onto the same basis set, yielding a second vector of coefficients (the 'spectral image'). A simple correlation coefficient is generated from the two vectors, providing a measure of co-linearity of the spectral template and the spectral image: higher correlation values indicate greater co-linearity. Exceeding a correlation threshold results in a target implemented--a single 32-megabyte bipolar SAR image can be processed in less than five minutes. Initial spectral-correlation efforts focused on canonical targets and the results have been widely reported. Current studies are focusing on tactical targets, such as CUCVs. Early results on CUCVs have shown that sa single resonance-based template can be sued effectively in the recognition of tactical targets. Ongoing studies have demonstrated a substantial reduction in the false-alarm rate over results reported previously. These results, as well as improvements in the recognitions-processing stage, are reported in this paper.

Paper Details

Date Published: 10 June 1996
PDF: 7 pages
Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); doi: 10.1117/12.242031
Show Author Affiliations
Vincent Sabio, Army Research Lab. (United States)


Published in SPIE Proceedings Vol. 2757:
Algorithms for Synthetic Aperture Radar Imagery III
Edmund G. Zelnio; Robert J. Douglass, Editor(s)

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