• DocumentCode
    2832108
  • Title

    Densification algorithm research on gravity gradiometer reference map generation

  • Author

    Yao, Zou ; Xiaorong, Shen

  • Author_Institution
    Dept. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
  • fYear
    2012
  • fDate
    June 30 2012-July 2 2012
  • Firstpage
    315
  • Lastpage
    320
  • Abstract
    Gravity gradient aided inertial navigation system is of a great significance for long-endurance passive automatic navigation. Under the circumstance that the actual gravity gradient data cannot be measured with the gradiometer, the map generation methods calculated by digital elevation model were researched. In order to generate high-resolution full-tensor gravity gradient maps, several densification algorithms, such as the Lagrange Interpolation Method, the Cubic Convolution Interpolation Method, the Improved Shepard Interpolation Method and the Radial Basis Function Interpolation Method were presented and compared.
  • Keywords
    cartography; convolution; densification; inertial navigation; interpolation; radial basis function networks; Lagrange interpolation method; cubic convolution interpolation method; densification algorithm research; gravity gradient aided inertial navigation system; gravity gradiometer reference map generation; high-resolution full-tensor gravity gradient maps; improved Shepard interpolation method; long-endurance passive automatic navigation; radial basis function interpolation method; Convolution; Gravity; Interpolation; Navigation; Polynomials; Root mean square; Standards; Densification Algorithm; Digital Elevation Model; Gravity Gradient Reference Map;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Science and Engineering (ICSSE), 2012 International Conference on
  • Conference_Location
    Dalian, Liaoning
  • Print_ISBN
    978-1-4673-0944-8
  • Electronic_ISBN
    978-1-4673-0943-1
  • Type

    conf

  • DOI
    10.1109/ICSSE.2012.6257198
  • Filename
    6257198