Recurrent Networks for Integrated Navigation
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.
KeywordsHide Layer Kalman Filter Recurrent Network Time Series Prediction Recurrent Connection
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