DocumentCode
1635645
Title
State Estimation of ALV Integrated Navigation System Based on BP Neural Network
Author
Wang, Meiling ; Fu, Yongwei
Author_Institution
Dept. of Autom. Control, Beijing Inst. of Technol., Beijing
Volume
2
fYear
2008
Firstpage
682
Lastpage
686
Abstract
In this paper, a data fusion method based on BP neural network and DR is proposed for ALV´s navigation. Mathematical models have been established for data fusion. When GPS is valid, neural network is adopted, which is three layered network with 5 input/ 3 output neurons with a single hidden layer. When GPS is invalid, DR is introduced by using outputs of IMU and milometer and initial information from BP network. Training and simulation are made with this BP network using the BP network program compiled with MATLAB, and experimental results indicate that the accuracy of integrated system has been improved in comparison with separate GPS and DR (navigation accuracy of DR has not been shown in this paper).
Keywords
Global Positioning System; artificial intelligence; backpropagation; control engineering computing; mobile robots; neural nets; path planning; sensor fusion; vehicles; BP neural network; GPS; autonomous land vehicle navigation system; data fusion method; state estimation; Fault tolerance; Gaussian noise; Global Positioning System; MATLAB; Mathematical model; Navigation; Neural networks; Parallel processing; State estimation; Working environment noise; BP neural network; Data fusion; Global positioning system; Integrated navigation system;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on
Conference_Location
Kaohsiung
Print_ISBN
978-0-7695-3382-7
Type
conf
DOI
10.1109/ISDA.2008.97
Filename
4696414
Link To Document