Paper Title:
Research on Seamless INS/GPS Integrated Navigation Algorithm
  Abstract

This paper proposed and discussed an INS/GPS integrated navigation method based on radial basis function neural network (RBFNN) to fuse INS and GPS data. When GPS signals were available, an adaptive Kalman filter was used to improve the estimation accuracy of INS errors, and then the RBFNN structure was trained to mimic the dynamical error model of INS. If GPS signals were unavailable, the trained RBFNN structure was utilized to bridge the GPS outages to achieve seamless navigation. Simulations in INS/GPS integrated navigation system showed the proposed method can reduce the positioning error during GPS outages.

  Info
Periodical
Advanced Materials Research (Volumes 299-300)
Edited by
Jianzhong Wang and Jingang Qi
Pages
1178-1181
DOI
10.4028/www.scientific.net/AMR.299-300.1178
Citation
T. L. Xu, Y. Tian, "Research on Seamless INS/GPS Integrated Navigation Algorithm", Advanced Materials Research, Vols. 299-300, pp. 1178-1181, 2011
Online since
July 2011
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Price
$32.00
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