DocumentCode
2710172
Title
Modeling random gyro drift by time series neural networks and by traditional method
Author
Xiyuan, Chen
Author_Institution
Dept. of Instrum. Sci. & Eng., Southeast Univ., Nanjing, China
Volume
1
fYear
2003
fDate
14-17 Dec. 2003
Firstpage
810
Abstract
This paper presents modeling random gyro drift rate by traditional time series method , and makes compensation for gyro drift by Kalman filter, and proposes the modeling and forecasting method by neural networks for strapdown gyro based on time series analysis, and makes a research for random drift rate of gyro applied for strapdown inertial navigation systems, comparison between the results of by Kalman filter based traditional time series method and by time series neural networks is presented.
Keywords
Kalman filters; inertial navigation; neural nets; time series; Kalman filter; neural networks; random gyro drift rate; strapdown inertial navigation systems; traditional time series method; Autocorrelation; Cities and towns; Error analysis; Inertial navigation; Instruments; Mathematical model; Neural networks; Predictive models; Testing; Time series analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location
Nanjing
Print_ISBN
0-7803-7702-8
Type
conf
DOI
10.1109/ICNNSP.2003.1279399
Filename
1279399
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