DocumentCode :
508007
Title :
GPS/DR Navigation Data Fusion Research Using Neural Network
Author :
Wang, Jingkun ; Zhang, Yuanliang ; Chong, Kil To
Author_Institution :
Sch. of Mech. Eng., Shandong Univ., Jinan, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
58
Lastpage :
61
Abstract :
It is well known that GPS can be used for localization and navigation in outside environment. Standard DGPS can be used to get an accuracy of under one meter. The precision improves but the cost is very high. The cheep single frequency GPS receiver is used in this paper to provide the positioning information. This paper proposes a new navigation data fusion method using neural network. DR (dead reckoning) navigation system can provide precise short term navigation information. But the error can accumulate over time without limitation. A BP neural network is employed to predict next sampling time GPS output and a new Kalman filter based data fusion method is proposed to do the navigation data fusion with GPS/DR system. Simulation is conducted to validate the proposed fusion method. The result shows the potential of this fusion method for outside used mobile robot navigation.
Keywords :
Global Positioning System; Kalman filters; backpropagation; neural nets; sensor fusion; telecommunication computing; BP neural network; GPS/DR navigation data fusion; Kalman filter; dead reckoning navigation system; positioning information; short term navigation information; single frequency GPS receiver; standard DGPS; Computer networks; Dead reckoning; Frequency; Geometry; Global Positioning System; Mobile robots; Neural networks; Satellite navigation systems; Sensor systems; Wheels; BP neural network; Kalman filter; integrated GPS/DR system; navigation data fusion;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.444
Filename :
5364624
Link To Document :
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