Compressed sensing-based frequency selection for classification of ground penetrating radar signals

Wenbin Shao*, Abdesselam Bouzerdoum, Son Lam Phung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

In this paper we present an automatic classification system for ground penetrating radar (GPR) signals. The system extracts the magnitude spectra at resonant frequencies and classifies them using support vector machines. To locate the resonant frequencies, we propose an approach based on compressed sensing and orthogonal matching pursuit. The performance of the system is evaluated by classifying GPR traces from different ballast fouling conditions. The experimental results show that the proposed approach, compared to the approach of using frequencies at local maxima, represents the GPR signal more efficiently using a small number of coefficients, and obtains higher classification accuracy.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages3377-3380
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: 25 Mar 201230 Mar 2012

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/TerritoryJapan
CityKyoto
Period25/03/1230/03/12

Keywords

  • compressed sensing
  • frequency selection
  • ground penetrating radar
  • pattern classification

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