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A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar

Publication ,  Journal Article
Malof, JM; Reichman, D; Karem, A; Frigui, H; Ho, KC; Wilson, JN; Lee, WH; Cummings, WJ; Collins, LM
Published in: IEEE Transactions on Geoscience and Remote Sensing
September 1, 2019

In this paper, we consider the development of algorithms for the automatic detection of buried threats using ground penetrating radar (GPR) measurements. GPR is one of the most studied and successful modalities for automatic buried threat detection (BTD), and a large variety of BTD algorithms have been proposed for it. Despite this, large-scale comparisons of GPR-based BTD algorithms are rare in the literature. In this paper, we report the results of a multi-institutional effort to develop advanced BTD algorithms for a real-world GPR BTD system. The effort involved five institutions with substantial experience with the development of GPR-based BTD algorithms. In this paper, we report the technical details of the advanced algorithms submitted by each institution, representing their latest technical advances, and many state-of-the-art GPR-based BTD algorithms. We also report the results of evaluating the algorithms from each institution on the large experimental data set used for development. The experimental data set comprised 120 000 m2 of GPR data using surface area, from 13 different lanes across two U.S. test sites. The data were collected using a vehicle-mounted GPR system, the variants of which have supplied data for numerous publications. Using these results, we identify the most successful and common processing strategies among the submitted algorithms, and make recommendations for GPR-based BTD algorithm design.

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Published In

IEEE Transactions on Geoscience and Remote Sensing

DOI

EISSN

1558-0644

ISSN

0196-2892

Publication Date

September 1, 2019

Volume

57

Issue

9

Start / End Page

6929 / 6945

Related Subject Headings

  • Geological & Geomatics Engineering
  • 40 Engineering
  • 37 Earth sciences
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0404 Geophysics
 

Citation

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Malof, J. M., Reichman, D., Karem, A., Frigui, H., Ho, K. C., Wilson, J. N., … Collins, L. M. (2019). A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar. IEEE Transactions on Geoscience and Remote Sensing, 57(9), 6929–6945. https://doi.org/10.1109/TGRS.2019.2909665
Malof, J. M., D. Reichman, A. Karem, H. Frigui, K. C. Ho, J. N. Wilson, W. H. Lee, W. J. Cummings, and L. M. Collins. “A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar.” IEEE Transactions on Geoscience and Remote Sensing 57, no. 9 (September 1, 2019): 6929–45. https://doi.org/10.1109/TGRS.2019.2909665.
Malof JM, Reichman D, Karem A, Frigui H, Ho KC, Wilson JN, et al. A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar. IEEE Transactions on Geoscience and Remote Sensing. 2019 Sep 1;57(9):6929–45.
Malof, J. M., et al. “A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar.” IEEE Transactions on Geoscience and Remote Sensing, vol. 57, no. 9, Sept. 2019, pp. 6929–45. Scopus, doi:10.1109/TGRS.2019.2909665.
Malof JM, Reichman D, Karem A, Frigui H, Ho KC, Wilson JN, Lee WH, Cummings WJ, Collins LM. A large-scale multi-institutional evaluation of advanced discrimination algorithms for buried threat detection in ground penetrating radar. IEEE Transactions on Geoscience and Remote Sensing. 2019 Sep 1;57(9):6929–6945.

Published In

IEEE Transactions on Geoscience and Remote Sensing

DOI

EISSN

1558-0644

ISSN

0196-2892

Publication Date

September 1, 2019

Volume

57

Issue

9

Start / End Page

6929 / 6945

Related Subject Headings

  • Geological & Geomatics Engineering
  • 40 Engineering
  • 37 Earth sciences
  • 0909 Geomatic Engineering
  • 0906 Electrical and Electronic Engineering
  • 0404 Geophysics