Underground Structures and Gravity Gradiometry

Abstract

This report evaluates the use of gravity gradiometry as a tool to characterize underground facilities. The gradient of the Earth's gravitational field can be used to make inferences about the Earth's mass density field. Mass deficits, such as those produced when an underground region is excavated, produce a characteristic change in the Earth's gravitational field. In principle, gradiometric measurements can make inferences about mass deficits that are covered by hundreds of meters of rock. In practice, the technique is much more limited. The report studies the potential for characterizing underground facilities from gravity data using matched filters and a variety of inversion techniques. All of the techniques indicate that the fundamental spatial resolution is directly related to the distance from the point of interest to the gradient sensor. Thus, resolution of feature sizes of man-made facilities requires quite close access by the gradient sensors. Detection applications are also limited by the unknown size of spatial gravity 'clutter' due to the inhomogeneous Earth. Useful applications may be possible where high-sensitivity instruments can be used in proximity to the area of interest. Measurements from high-altitude aircraft or space may be strongly synergistic with short-distance measurements.

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Document Details

Document Type
Technical Report
Publication Date
Jan 15, 2002
Accession Number
ADA400252

Entities

People

  • M. W. Maier

Organizations

  • The Aerospace Corporation

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force Research Laboratories
  • Aircrafts
  • Algorithms
  • Altitude
  • Change Detection
  • Coordinate Systems
  • Detection
  • Detectors
  • Geometry
  • Gradiometers
  • Gravitational Fields
  • Jet Propulsion
  • Matched Filters
  • Measurement
  • Underground Facilities
  • Underground Structures
  • Warning Systems

Fields of Study

  • Physics

Readers

  • Geotechnical Engineering.
  • Plasma Physics / Magnetohydrodynamics
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • Space
  • Space - Orbital Debris
  • Space - Space Objects