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.

Meeting Name

14th International Conference on Ground Penetrating Radar (2012: Jun 4-8, Shanghai, China)


Electrical and Computer Engineering

Second Department

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)


Document Type

Article - Conference proceedings

Document Version


File Type





© 2012 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2012