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
fDate :
June 30 2012-July 2 2012
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;
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
DOI :
10.1109/ICSSE.2012.6257198