Recurrent networks for integrated navigation

Authors:
Jianguo Fu;Yingcai Wang;Jianhua Li;Zhenyu Zheng;Xingbo Yin
Affiliations:
Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, China;Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, China;Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, China;Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, China;Department of Navigation, Dalian Naval Academy, Dalian, Liaoning, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Year:
2005

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Kalman Filtering and Neural Networks

Kalman Filtering and Neural Networks

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Abstract

A novel neural-network-compensated Kalman filter for integrated navigation system was proposed. Based on the similarity of operation principle between Elman networks and non-linear ARMA model, the Elman network is employed as a compensating error estimator to improve accuracy of the Kalman filter. The proposed architecture is evaluated with the acquired data from a naval vessel. And the results show that the presented method can markedly attenuate the effect of interferes to Kalman filter, and improve the precision of the integrated navigation system.