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Proceedings Paper

Detecting 1/10th scaled structures in dielectric media using monostatic X-band radar scattering measurements
Author(s): John D. Kekis; Markus E. Testorf; Michael A. Fiddy; Robert H. Giles
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Paper Abstract

Under the sponsorship of the U.S. Army's National Ground Intelligence Center (NGIC), researchers at U. Mass. Lowell's Submillimeter-Wave Technology Laboratory (STL) and Center for Electromagnetic Materials and Optical Systems (CEMOS) investigated the feasibility of detecting non-metallic structures embedded in various types of soil using a 1-GHz ground penetrating radar by establishing a 1/10th-scale laboratory environment with two spot-focusing X-band (10- GHz) lens antennae and an HP8510B Network Analyzer. Achieving similitude with the full-scale environment required fabricating replicas that were dimensional and dielectric scale-models of the non-metallic structures of interest (i.e. anti-personnel mines), as well as rocks, and soil with various levels of moisture content. The 1/10th- scale replicas were constructed form models at 10.0-GHz. The monostatic X-band measurements were acquired in an anechoic environment, and digital images of the backscattered radar data from the 1/10th-scale composite scenes were processed using inverse synthetic aperture radar (ISAR) signal processing routines, and also PDFT superresolution imaging techniques. Based on the 1/10th-scale signature measurements performed, the feasibility of detecting a VS-50 anti-personnel mine buried in dry loam at a depth of 11.2mm was established. The full-scale radar cross-section of a VS=50 mine in this configuration was estimated to be -25 dBsm. Radar cross section values were not established for the structures embedded in the wet loam due to a change in the intensity scale (an inherent property of the superresolution algorithm), which changed for each image. However, the embedded objects were detected by the PDFT algorithm, showing promise for the future of this research.

Paper Details

Date Published: 16 November 2000
PDF: 12 pages
Proc. SPIE 4123, Image Reconstruction from Incomplete Data, (16 November 2000); doi: 10.1117/12.409277
Show Author Affiliations
John D. Kekis, Univ. of Massachusetts/Lowell (United States)
Markus E. Testorf, Univ. of Massachusetts/Lowell (United States)
Michael A. Fiddy, Univ. of Massachusetts/Lowell (United States)
Robert H. Giles, Univ. of Massachusetts/Lowell (United States)


Published in SPIE Proceedings Vol. 4123:
Image Reconstruction from Incomplete Data
Michael A. Fiddy; Rick P. Millane, Editor(s)

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