Conceptual Model for Prediction of Magnetic Soil Properties

Abstract

Recent studies have demonstrated the potentially serious impact of magnetic soils on the detection of buried objects such as land mines and unexploded ordnance (UXO) using magnetometers and electromagnetic inductions sensors, two methods that are routinely used in clearance operations. Magnetic soils can cause both equipment malfunctions and an increase in false alarms due to the presence of anomalies that have a geologic or pedogenic origin. To improve the discrimination performance of land mine and UXO detection sensors, there is a need for a better understanding of the natural variability in magnetic characteristics of soils. This research addressed this need by develop a conceptual model for the prediction of magnetic characteristics of soils developed on a wide range of geological parent materials, of different ages, and in diverse climatological environments. The research provides the Army with a new approach to the non-intrusive geophysical characterization of subsurface materials and their spatial distribution; the prediction of location, frequency, and scale of subsurface heterogeneity. The conceptual model that we have developed will allow for a better prediction of sensor capabilities in many iron-oxide containing field soils.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 13, 2005
Accession Number
ADA443302

Entities

People

  • Brian Borchers
  • Remke Van Dam

Organizations

  • New Mexico Institute of Mining and Technology

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Detection
  • Detectors
  • Drainage Basins
  • Ecology
  • Electromagnetic Induction
  • False Alarms
  • Frequency
  • Iron
  • Iron Oxides
  • Land Mines
  • Magnetic Properties
  • Materials
  • New Mexico
  • Spatial Distribution
  • Unexploded Ammunition
  • Uxo Detection
  • Warning Systems

Readers

  • Computational Modeling and Simulation
  • Military/Explosive Ordnance Disposal (EOD) Technology
  • Sensor Fusion and Tracking Systems.