3 May 2016 Preprocessing of A-scan GPR data based on energy features
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Abstract
There is an increasing demand for noninvasive real-time detection and classification of buried objects in various civil and military applications. The problem of detection and annihilation of landmines is particularly important due to strong safety concerns. The requirement for a fast real-time decision process is as important as the requirements for high detection rates and low false alarm rates. In this paper, we introduce and demonstrate a computationally simple, timeefficient, energy-based preprocessing approach that can be used in ground penetrating radar (GPR) applications to eliminate reflections from the air-ground boundary and to locate the buried objects, simultaneously, at one easy step. The instantaneous power signals, the total energy values and the cumulative energy curves are extracted from the A-scan GPR data. The cumulative energy curves, in particular, are shown to be useful to detect the presence and location of buried objects in a fast and simple way while preserving the spectral content of the original A-scan data for further steps of physics-based target classification. The proposed method is demonstrated using the GPR data collected at the facilities of IPA Defense, Ankara at outdoor test lanes. Cylindrically shaped plastic containers were buried in fine-medium sand to simulate buried landmines. These plastic containers were half-filled by ammonium nitrate including metal pins. Results of this pilot study are demonstrated to be highly promising to motivate further research for the use of energy-based preprocessing features in landmine detection problem.
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Mesut Dogan, Gonul Turhan-Sayan, "Preprocessing of A-scan GPR data based on energy features", Proc. SPIE 9823, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXI, 98231E (3 May 2016); doi: 10.1117/12.2223946; https://doi.org/10.1117/12.2223946
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