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Proceedings Paper

Signal processing approaches to radio frequency interference (RFI) suppression
Author(s): Matthew Braunstein; James M. Ralston; David A. Sparrow
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Paper Abstract

Ultra-wideband radar (UWB) has been shown to be among the most powerful techniques available for underground and obscured object detection. The value of such systems is that they combine the penetration enhancement associated with VHF/UHF (and lower) frequencies with the resolution of wide absolute bandwidth. Such systems necessarily make use of much of the frequency spectrum already in heavy use by other services, such as television and mobile communications. Although this spectral overlap provides occasion for adverse consequences in both directions, to date the principal consequence has been often-severe impact on UWB radar measurements. Even in remote locations, the average interference power often exceeds receiver noise by many dB, becoming the limiting factor on system sensitivity. Nor are UWB radar designers free to overcome this interference by increasing radar power, since regulatory sanction for UWB operation will depend on maintaining sufficiently low spectral power densities to assure that other, prior, services are not appreciably degraded. Given the importance of radio frequency interference (RFI) on practical ultrawide band ground penetrating radar systems, it is important to consider how and to what extent the effects of RFI noise may be reduced. The overall problem of RFI and its impacts will be described and several signal processing approaches to removal of RFI will be discussed. These include spectral estimation and coherent subtraction algorithms and various filter approaches, which have been developed and applied by the signal processing community in other contexts. These methods will be applied to several different real-world experimental data sets, and quantitative measures of the effectiveness of each of these algorithms in removing RFI noise will be presented. Although computationally-intensive, most of the techniques to be described achieve substantial increases in S/RFI without requiring concomitant increases in radar average power.

Paper Details

Date Published: 9 June 1994
PDF: 19 pages
Proc. SPIE 2230, Algorithms for Synthetic Aperture Radar Imagery, (9 June 1994); doi: 10.1117/12.177172
Show Author Affiliations
Matthew Braunstein, Institute for Defense Analyses (United States)
James M. Ralston, Institute for Defense Analyses (United States)
David A. Sparrow, Institute for Defense Analyses (United States)


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

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