Statistical Signal Processing for Demining: Experimental Validation

Abstract

Under the support provided by ARO in the form of a MURI for Humanitiarian demining, successful techniques for discriminating between mines and anthropic clutter have been developed using a statistical signal processing approach. The improved performance provided by these algorithms has been validated using data obtained by DARPA. In order determine whether these algorithms have wider application than the relatively high-metallic content mines used in the DARPA experiment, the Joint UXO Coordination Office (JUXOCO) was interested in augmenting the work begun under the MURI. JUXOCO is sponsoring a series of experiments designed to establish a performance baseline for metallic mine detectors. This baseline will be used to measure the potential improvements in performance offered by advanced signal processing algorithms. The goal of the work funded under this grant was to collect data from low-metal content mine using Geophex's GEM-3 sensor and to begin the development of improved detection algorithms. This report provide a summary of the results obtained during the course of this study and a summary of experimental data acquisition methods.

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Document Details

Document Type
Technical Report
Publication Date
Jun 21, 1999
Accession Number
ADA370676

Entities

People

  • Leslie M. Collins

Organizations

  • Duke University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Sensors

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Data Acquisition
  • Data Analysis
  • Detection
  • Detectors
  • Electromagnetic Induction
  • Electromagnetic Induction Sensors
  • Experimental Data
  • False Alarms
  • Frequency Domain
  • Information Science
  • Land Mines
  • Signal Detection
  • Signal Processing
  • Unexploded Ammunition
  • Warning Systems

Readers

  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Research Science/Academic Research
  • Sensor Fusion and Tracking Systems.