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Proceedings Paper

Deconvolution techniques for passive radar imaging
Author(s): Aaron D. Lanterman; David C. Munson
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Paper Abstract

Forming images of aircraft using passive radar systems that exploit illuminators of opportunity, such as commercial television and FM radio systems, involves reconstructing an image from sparse samples of its Fourier transform. For a given flight path, a single receiver-transmitter pair produces one arc of data in Fourier space. Since the resulting Fourier sampling patterns bear a superficial resemblance to those found in radio astronomy, we consider using deconvolution techniques borrowed from radio astronomy, namely the CLEAN algorithm, to form images from passive radar data. Some deconvolution techniques, such as the CLEAN algorithm, work best on images which are well-modeled as a set of distinct point scatterers. Hence, such algorithms are well-suited to high-frequency imaging of man-made targets, as the current on the scatterer surface tends to collect at particular points. When using low frequencies of interest in passive radar, the images are more distributed. In addition, the complex-valued nature of radar imaging presents a complication not present in radio astronomy, where the underlying images are real valued. These effects conspire to present a great challenge to the CLEAN algorithm, indicating the need to explore more sophisticated techniques.

Paper Details

Date Published: 1 August 2002
PDF: 12 pages
Proc. SPIE 4727, Algorithms for Synthetic Aperture Radar Imagery IX, (1 August 2002); doi: 10.1117/12.478688
Show Author Affiliations
Aaron D. Lanterman, Georgia Institute of Technology (United States)
David C. Munson, Univ. of Illinois/Urbana-Champaign (United States)


Published in SPIE Proceedings Vol. 4727:
Algorithms for Synthetic Aperture Radar Imagery IX
Edmund G. Zelnio, Editor(s)

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