Sensor integration study for a shallow tunnel detection system.

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During the past several years, there has been a growing recognition of the threats posed by the use of shallow tunnels against both international border security and the integrity of critical facilities. This has led to the development and testing of a variety of geophysical and surveillance techniques for the detection of these clandestine tunnels. The challenges of detection of these tunnels arising from the complexity of the near surface environment, the subtlety of the tunnel signatures themselves, and the frequent siting of these tunnels in urban environments with a high level of cultural noise, have time and again shown ... continued below

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43 p.

Creation Information

Yee, Mark L.; Abbott, Robert E.; Bonal, Nedra; Elbring, Gregory Jay & Senglaub, Michael E. February 1, 2010.

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Description

During the past several years, there has been a growing recognition of the threats posed by the use of shallow tunnels against both international border security and the integrity of critical facilities. This has led to the development and testing of a variety of geophysical and surveillance techniques for the detection of these clandestine tunnels. The challenges of detection of these tunnels arising from the complexity of the near surface environment, the subtlety of the tunnel signatures themselves, and the frequent siting of these tunnels in urban environments with a high level of cultural noise, have time and again shown that any single technique is not robust enough to solve the tunnel detection problem in all cases. The question then arises as to how to best combine the multiple techniques currently available to create an integrated system that results in the best chance of detecting these tunnels in a variety of clutter environments and geologies. This study utilizes Taguchi analysis with simulated sensor detection performance to address this question. The analysis results show that ambient noise has the most effect on detection performance over the effects of tunnel characteristics and geological factors.

Physical Description

43 p.

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  • Report No.: SAND2010-0901
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/984150 | External Link
  • Office of Scientific & Technical Information Report Number: 984150
  • Archival Resource Key: ark:/67531/metadc1012432

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Office of Scientific & Technical Information Technical Reports

Reports, articles and other documents harvested from the Office of Scientific and Technical Information.

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Creation Date

  • February 1, 2010

Added to The UNT Digital Library

  • Oct. 14, 2017, 8:36 a.m.

Description Last Updated

  • Oct. 25, 2017, 4:31 p.m.

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Yee, Mark L.; Abbott, Robert E.; Bonal, Nedra; Elbring, Gregory Jay & Senglaub, Michael E. Sensor integration study for a shallow tunnel detection system., report, February 1, 2010; United States. (digital.library.unt.edu/ark:/67531/metadc1012432/: accessed July 20, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.