Paper
18 May 2006 Predicting GPR target locations using time delay differences
Author Affiliations +
Abstract
We describe an efficient approach for finding probable target areas quickly with a minimal number of Ground Penetrating Radar (GPR) measurements. Since a potential GPR target creates a hyperbolic signature in the space-time domain, our approach uses the time delay differences from consecutive GPR A-Scan data to estimate the location of the apex of the hyperbolic signature, thus locating a target. This apex prediction method uses many fewer measurements than a full backprojection algorithm. Regions of low target probability are determined using a Neyman-Pearson detection approach in order to eliminate redundant measurements. In this regard, our approach is especially suitable as a pre-screener: other sensors that are more accurate, but require more measurement time, can then be applied only to high probability-of-target areas to corroborate results, differentiate between targets, or provide more accurate location measurements. Compared to a standard backprojection algorithm more signal-to-noise ratio (SNR) is needed to achieve similar detection performance. This SNR loss can be reduced by using a more conservative algorithm which reduces the step size of the GPR antenna. Results from experimental data collected at a model mine field at the Georgia Institute of Technology show that target positions can be found accurately using less than 10% of the measurements utilized by conventional imaging algorithms.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ali Cafer Gürbüz, James H. McClellan, and Waymond R. Scott Jr. "Predicting GPR target locations using time delay differences", Proc. SPIE 6217, Detection and Remediation Technologies for Mines and Minelike Targets XI, 621731 (18 May 2006); https://doi.org/10.1117/12.666335
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Target detection

Antennas

General packet radio service

Signal to noise ratio

Mining

Data modeling

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