Target Picking Methods for Magnetic Data

Abstract

Due to the large numbers (up to tens of thousands) of possible targets identified in nominal unexploded ordnance (UXO) surveys, efficient and reliable machine-aided target pickers should be used to identify targets for subsequent characterization. When selecting anomalies, the goal is to identify all anomalous features that may be caused by UXO, while minimizing operator time and eliminating operator bias. To facilitate advanced physics-based modeling, however, the target pickers should also be able to select data appropriate to the target, i.e., to outline or estimate the anomaly's spatial extent. The current approach to target selection is either manual identification or amplitude thresholding. The former is time-intensive, not clearly defined, and prone to operator bias. The latter is sensitive to noise and is prone to over- or under-picking unless judicious oversight is exercised. Neither approach provides measures for estimating the footprint of the anomaly. The impact to the Department of Defense (DoD) is obvious. Systematic, fast, and robust target pickers can save money and produce a defensible target list compared to the current methods.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2008
Accession Number
ADA495495

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Background Noise
  • Bombs
  • Data Analysis
  • Data Sets
  • Department Of Defense
  • Detection
  • Detectors
  • Environmental Security
  • Explosives
  • False Alarms
  • General Purpose Bombs
  • Global Positioning Systems
  • Magnetometers
  • Munitions
  • Unexploded Ammunition
  • Warning Systems

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Modeling and Simulation
  • Military/Explosive Ordnance Disposal (EOD) Technology