GPR Detection of Buried Symmetrically Shaped Mine-like Objects using Selective Independent Component Analysis

Brian Karlsen, Helge B.D. Sørensen, Jan Larsen, Kaj B. Jakobsen

AbstractThis paper addresses the detection of mine-like objects in
stepped-frequency ground penetrating radar (SF-GPR) data as a
function of object size, object content, and burial depth. The
detection approach is based on a Selective Independent Component
Analysis (SICA). SICA provides an automatic ranking of components,
which enables the suppression of clutter, hence extraction of
components carrying mine information. The goal of the investigation
is to evaluate various time and frequency domain ICA approaches
based on SICA. Performance comparison is based on a series of
mine-like objects ranging from small-scale anti-personal (AP) mines
to large-scale anti-tank (AT) mines were designed. Large-scale
SF-GPR measurements on this series of mine-like objects buried in
soil were performed. The SF-GPR data was acquired using a wideband
monostatic bow-tie antenna operating in the frequency range
750 MHz- 3.0 GHz. The detection and clutter
reduction approaches based on SICA are successfully evaluated on
this SF-GPR dataset.
KeywordsGPR ICA stepped frequency landmine
TypeConference paper [With referee]
ConferenceProceedings of the 2003 Detection and Remediation Technologies for Mines and Mine-Like Targets, AeroSense 2003
Year2003    Month April    Vol. 5089    pp. 375-386
AddressOrlando FL
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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