Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection

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Abstract

This paper presents statistical signal processing approaches for clutter reduction in stepped-frequency ground penetrating radar (SF-GPR) data. In particular, we suggest clutter/signal separation techniques based on principal and independent component analysis (PCA/ICA). The approaches are successfully evaluated and compared on a real SF-GPR time-series. Field-test data are acquired using a monostatic S-band rectangular waveguide antenna.
Original languageEnglish
Title of host publicationProceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Orchid Country Club, Singapore
PublisherIEEE
Publication date2001
Pages146-149
ISBN (Print)0-7803-7011-2
DOIs
Publication statusPublished - 2001
EventIEEE Signal Processing Workshop on Statistical Signal Processing -
Duration: 1 Jan 2001 → …
Conference number: 11th

Conference

ConferenceIEEE Signal Processing Workshop on Statistical Signal Processing
Number11th
Period01/01/2001 → …

Bibliographical note

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Cite this

Karlsen, B., Larsen, J., Sørensen, H. B. D., & Jakobsen, K. B. (2001). Comparison of PCA and ICA based clutter reduction in GPR systems for anti-personal landmine detection. In Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, Orchid Country Club, Singapore (pp. 146-149). IEEE. https://doi.org/10.1109/SSP.2001.955243