Application of Ground Penetrating Radar Technology for Near-surface Interface Determination in Coal Mining
Strange, Andrew D., Ralston, Jonathon C., & Chandran, Vinod (2005) Application of Ground Penetrating Radar Technology for Near-surface Interface Determination in Coal Mining. In IEEE International Conference on Acoustics, Speech, and Signal Processing, 18-23 March, 2005, Philadelphia, PA, USA.
The use of ground penetrating radar (GPR) for detecting near-surface interfaces is a scenario of special interest to the underground coal mining industry. The problem is
difficult to solve in practice because the radar echo is often dominated by unwanted components such as antenna crosstalk and ringing, ground-bounce effects,
clutter, and severe attenuation. These nuisance components are also highly sensitive to subtle variations in ground conditions, rendering the application of standard signal pre-processing techniques largely ineffective in the unsupervised case. As a solution to this problem, we develop a novel algorithm which utilizes a pattern recognition-based approach using features derived from the bispectrum of the radar data. We show that,
unlike traditional second order correlation based methods such as matched filtering which fail in known conditions, the new method reliably allows the determination of layer
interfaces using GPR to be extended to the near surface region.
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
Repository Staff Only: item control page