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An Improved Post-Processing Technique for Array-Based Detection of Underground Tunnels

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5 Author(s)
Peng Xie ; Intel Corp., Santa Clara, CA, USA ; Grant, S.L. ; Putnam, N.H. ; Anderson, N.L.
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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. To address this problem, this work proposes a data acquisition scheme and develops a new post-processing approach. The first applied measure estimates the confidence level of each detection result. The second processes the data in sub-arrays, and filters out false alarms. The third scans all detections and searches the cluster with the highest cumulative confidence level. This paper provides engineering practitioners with a simple and efficient method to reliably determine tunnel locations. Experimental results derived from data recorded in various testing sites and surface conditions verify the effectiveness of this work.

Published in:

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of  (Volume:7 ,  Issue: 3 )

Date of Publication:

March 2014

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