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Proceedings Paper

Independent component analysis for clutter reduction in ground penetrating radar data
Author(s): Brian Karlsen; Helge B.D. Sorensen; Jan Larsen; Kaj Bjarne Jakobsen
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Paper Abstract

Statistical signal processing approaches based on Independent Component Analysis (ICA) algorithms for clutter reduction in Stepped-Frequency Ground Penetrating Radar (SF-GPR) data are presented. The purpose of the clutter reduction is indirectly to decompose the GPR data into clutter reduced GPR data and clutter. The experiments indicate that ICA algorithms can decompose GPR data into suitable subspace components, which makes it possible to select a subset of components containing primarily target information (like anti-personal landmines) and others which contain mainly clutter information. The paper compares spatial and temporal ICA approaches on field-test data from shallow buried iron and plastic anti-personal landmines. The data are acquired using a monostatic bow-tie antenna operating in the frequency range from 500 MHz to 2.5 GHz.

Paper Details

Date Published: 13 August 2002
PDF: 12 pages
Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); doi: 10.1117/12.479110
Show Author Affiliations
Brian Karlsen, Technical Univ. of Denmark (Denmark)
Helge B.D. Sorensen, Technical Univ. of Denmark (Denmark)
Jan Larsen, Technical Univ. of Denmark (Denmark)
Kaj Bjarne Jakobsen, Technical Univ. of Denmark (Denmark)

Published in SPIE Proceedings Vol. 4742:
Detection and Remediation Technologies for Mines and Minelike Targets VII
J. Thomas Broach; Russell S Harmon; Gerald J. Dobeck, Editor(s)

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