Advanced EMI Models and Classification Algorithms: The Next Level of Sophistication to Improve Discrimination of Challenging Targets

Abstract

This project yields combined software/hardware approaches for enhancing the detection and classification of small and/or deep targets at live UXO sites. Advanced EMI models were adapted to existing hardware, hardware electronics were modified to increase EMI responsesfrom buried targets, and modified hardware/software performance was evaluated using test-stand and blind data sets. The combinedapproach detected and classified all shallow targets and also managed to detect and classify small targets buried as deep as 20 times thetarget diameter. The high-power transmitter system developed here has been implemented in the Geometrics mini MetalMapper, acommercially available version of the 2 2 TEMTADS.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2017
Accession Number
AD1037127

Entities

People

  • Benjamin E. Barrowes
  • Daniel Stienhurst
  • Dave George
  • Fridon Shubitidze
  • Juan P. Fernandez
  • Thomas Bell

Organizations

  • Dartmouth College

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Data Sets
  • Detection
  • Detectors
  • Electrical Properties
  • Electromagnetic Induction
  • Electromagnetic Induction Sensors
  • Geometry
  • Information Science
  • Magnetic Fields
  • Munitions
  • Munitions Testing
  • Pattern Recognition
  • Supervised Machine Learning
  • Test Stands
  • Transmitters
  • Unexploded Ammunition
  • Uxo Detection

Readers

  • Distributed Systems and Data Platform Development
  • Military/Explosive Ordnance Disposal (EOD) Technology

Technology Areas

  • Microelectronics
  • Microelectronics - Microelectromechanical Systems