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How transferable are downward-looking and handheld ground penetrating radar data? Experiments in the context of buried threat detection
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Paper Abstract

In this work we consider the problem of developing algorithms for the automatic detection of buried threats using handheld Ground Penetrating Radar (HH-GPR) data. The development of algorithms for HH-GPR is relatively nascent compared to algorithm development efforts for larger downward-looking GPR (DL-GPR) systems. One of the biggest bottlenecks for the development of algorithms is the relative scarcity of labeled HH-GPR data that can be used for development. Given the similarities between DL-GPR data and HH-GPR data however, we hypothesized that it may be possible to utilize DL-GPR data to support the development of algorithms for HH-GPR. In this work we assess the detection performance of a HH-GPR-based BTD algorithm as we vary the amounts and characteristics of the DL-GPR data included in the development of HH-GPR detection algorithms. The results indicate that supplementing HH-GPR data with DL-GPR does improve performance, especially when including data collected over buried threat locations.

Paper Details

Date Published: 10 May 2019
PDF: 10 pages
Proc. SPIE 11012, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV, 110120G (10 May 2019); doi: 10.1117/12.2519969
Show Author Affiliations
Evan Stump, Duke Univ. (United States)
Daniel Reichman, Duke Univ. (United States)
Leslie M. Collins, Duke Univ. (United States)
Jordan M. Malof, Duke Univ. (United States)


Published in SPIE Proceedings Vol. 11012:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIV
Steven S. Bishop; Jason C. Isaacs, Editor(s)

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