Independent component analysis for clutter reduction in ground penetrating radar data

Brian Karlsen; Helge B.D. Sorensen; Jan Larsen; Kaj Bjarne Jakobsen

doi:10.1117/12.479110

13 August 2002 Independent component analysis for clutter reduction in ground penetrating radar data

Brian Karlsen, Helge B.D. Sorensen, Jan Larsen, Kaj Bjarne Jakobsen

Proceedings Volume 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII; (2002) https://doi.org/10.1117/12.479110
Event: AeroSense 2002, 2002, Orlando, FL, United States

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.

Citation Download Citation

Brian Karlsen, Helge B.D. Sorensen, Jan Larsen, and Kaj Bjarne Jakobsen "Independent component analysis for clutter reduction in ground penetrating radar data", Proc. SPIE 4742, Detection and Remediation Technologies for Mines and Minelike Targets VII, (13 August 2002); https://doi.org/10.1117/12.479110

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