Array Processing for Underground Tunnel Detection
This paper investigates challenges faced by many geophysical algorithms applied to real-world cases such as the Attenuation Analysis of Rayleigh Waves (AARW). AARW shows great promise in terms of detecting shallow underground tunnels. However, in-situ subsurface anomalies, including those due to anisotropy, and instrument sensitivity to natural conditions can significantly degrade the utility of this technique. The first applied measure estimates the confidence level of each detection result. The second processes the recorded data in sub-arrays, acting as a filter to remove false alarms. The third scans all detections and searches the cluster with the highest cumulative confidence level. A case study is presented to demonstrate the effectiveness of AARW along with post-processing quality control measures. This work provides engineering practitioners with a simple and efficient method to reliably determine tunnel locations.
P. Xie et al., "Array Processing for Underground Tunnel Detection," Proceedings of the 14th International Conference on Ground Penetrating Radar (2012, Shanghai, China), pp. 571-576, Institute of Electrical and Electronics Engineers (IEEE), Jun 2012.
The definitive version is available at http://dx.doi.org/10.1109/ICGPR.2012.6254929
14th International Conference on Ground Penetrating Radar (2012: Jun 4-8, Shanghai, China)
Electrical and Computer Engineering
Geosciences and Geological and Petroleum Engineering
Keywords and Phrases
AARW; Array processing; Attenuation analysis of Rayleigh waves; Mobile seismic unit; Tunnel detection; Confidence levels; Control measures; Engineering practitioners; False alarms; In-situ; Natural conditions; Post processing; Sub-arrays; Underground tunnels; Geological surveys; Ground penetrating radar systems; Rayleigh waves
International Standard Book Number (ISBN)
Article - Conference proceedings
© 2012 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.