• DocumentCode
    889463
  • Title

    Imaging Cargo Containers Using Gravity Gradiometry

  • Author

    Kirkendall, Barry ; Li, Yaoguo ; Oldenburg, Douglas

  • Author_Institution
    Colorado Sch. of Mines, Golden, CO
  • Volume
    45
  • Issue
    6
  • fYear
    2007
  • fDate
    6/1/2007 12:00:00 AM
  • Firstpage
    1786
  • Lastpage
    1797
  • Abstract
    Identifying fissile materials inside cargo shipping containers is a current national security need. We propose using the geophysical technique of gravity gradiometry to image cargo shipping containers for the purpose of detecting high-density materials. We focus on developing the necessary numerical algorithms and carrying out feasibility studies without being concerned with engineering, instrumentation, and application issues. To obtain realistic images with sharp boundaries, robust estimators are applied to the model objective function of the inversion operator and coupled with a Huber norm to provide stable numerical computation. We explicitly form the linear and nonlinear resolution matrices to quantify the resolution errors and perform a funnel analysis to quantify the variance of the recovered densities. Assuming a realistic data acquisition pattern requiring a reasonable amount of time, we show that it is possible to identify high-density materials with a minimum volume of 15 cm3. Finally, we provide a recovered density threshold to suggest the presence of high-density materials from an arbitrary recovered density model and apply this to two examples of recovering concealed fissile material from a cargo container
  • Keywords
    data acquisition; freight containers; gravity; inspection; national security; radioisotopes; Huber norm; cargo container imaging; cargo shipping containers; data acquisition pattern; fissile materials; gravity gradiometry; high-density materials; Biological materials; Containers; Electromagnetic induction; Geophysical measurements; Geophysics; Gravity measurement; Laboratories; Magnetic field measurement; Remote sensing; Robustness; Density image; gravity measurement; inverse problems; optimization methods; robustness;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2007.895427
  • Filename
    4215058