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Sparse signal decomposition for ground penetrating radar

Conference Paper


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Abstract


  • In this paper, we present an adaptive approach for sparse signal decomposition, in which each GPR trace is decomposed into elementary waves automatically. A sparse feature vector is extracted from the decomposition and used for classification of railway ballast. The experimental results show that the proposed approach can represent the GPR signals efficiently, and effective features can be extracted for pattern classification.

Publication Date


  • 2011

Citation


  • W. Shao, A. Bouzerdoum & S. Phung, "Sparse signal decomposition for ground penetrating radar," in 2011 IEEE Radar Conference, 2011, pp. 453-457.

Scopus Eid


  • 2-s2.0-80052514545

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2264&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1251

Start Page


  • 453

End Page


  • 457

Abstract


  • In this paper, we present an adaptive approach for sparse signal decomposition, in which each GPR trace is decomposed into elementary waves automatically. A sparse feature vector is extracted from the decomposition and used for classification of railway ballast. The experimental results show that the proposed approach can represent the GPR signals efficiently, and effective features can be extracted for pattern classification.

Publication Date


  • 2011

Citation


  • W. Shao, A. Bouzerdoum & S. Phung, "Sparse signal decomposition for ground penetrating radar," in 2011 IEEE Radar Conference, 2011, pp. 453-457.

Scopus Eid


  • 2-s2.0-80052514545

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=2264&context=infopapers

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/1251

Start Page


  • 453

End Page


  • 457