@inproceedings{4f60fa6d380f4a598e60c770f20ef5c7,
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.",
keywords = "INS, Integrated navigation system, Kalman filter, RBFNN",
author = "Tianlai Xu and Yang Tian",
year = "2011",
doi = "10.4028/www.scientific.net/AMR.299-300.1178",
language = "英语",
isbn = "9783037852019",
series = "Advanced Materials Research",
pages = "1178--1181",
booktitle = "Materials and Manufacturing",
note = "International Conference on Material and Manufacturing, ICMM 2011 ; Conference date: 07-09-2011 Through 09-09-2011",
}