Performance of conventional Kalman filter, which is used in integrated navigation system, depends on precise system model and accurate observation data. Inaccuracy system model or truseless observation data will cause low precision of Kalman filter, and even lead to divergence. So a new adaptive Kalman filter based on evolutionary artificial neural networks is used in this system. The algorithm is tested by simulations, and the results indicated that the algorithm proposed in this paper can efficiently overcome the shortcomings of conventional Kalman filter with better accuracy.
Application of evolutionary neural networks in integrated navigation system
01.12.2008
577821 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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