Prediction of DGPS corrections with neural networks

Author

Sang, Jizhang ; Kubik, Kurt ; Zhang, Lianggang

Author_Institution

Space Centre for Satellite Navigation, Queensland Univ. of Technol., Brisbane, Qld., Australia

Volume

2

fYear

1997

fDate

27-23 May 1997

Firstpage

355

Abstract

Applies neural network modelling to predicting DGPS (Differential Global Positioning System) corrections. The paper first briefly introduces GPS and DGPS navigation principles and aircraft navigation performance requirements. Following a discussion of the temporal characteristics of the DGPS corrections, a technique for predicting the DGPS corrections based on diagonal recurrent neural network (DRNN) modelling is presented. Numerical examples show that the prediction accuracy is better than 1 m for 10 s prediction and 1.3 m for 30 s prediction, respectively, which can maintain the aircraft navigation at the required accuracy for a period of 30 s

Keywords

Global Positioning System; aircraft computers; aircraft navigation; error correction; recurrent neural nets; 1 m; 1.3 m; 10 s; 30 s; DGPS correction prediction; Differential Global Positioning System; aircraft navigation performance requirements; diagonal recurrent neural network; neural network modelling; prediction accuracy; temporal characteristics; Aircraft navigation; Australia; Extraterrestrial measurements; Global Positioning System; Neural networks; Noise measurement; Predictive models; Satellite broadcasting; Satellite navigation systems; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Knowledge-Based Intelligent Electronic Systems, 1997. KES '97. Proceedings., 1997 First International Conference on

Conference_Location

Adelaide, SA

Print_ISBN

0-7803-3755-7

Type

conf

DOI

10.1109/KES.1997.619409

Filename

619409