A Geomagnetic Navigation Method Based on Neural Network Prediction Model Error
A geomagnetic model error prediction method based on artificial neural networks is proposed in response to the difficulty of improving geomagnetic navigation precision because of the slow update and low accuracy of the geomagnetic field model.The mapping relationship is combined with the magnetic field measurement data of on-orbit satellites to estimate and predict the geomagnetic field model error by establis-hing the relationship among geomagnetic field intensity vector elements,geographical features,and time in-formation.m addition,a geomagnetic navigation method combining neural network with filter is proposed.In order to verify the accuracy and effectiveness of this method,simulation verification is conducted by using satellite measured information.The results show that compared with the advanced filter method in recent years'literatures,the position and velocity accuracy can be improved from 4.15 km,4.38 m/s to 1.34 km,1.47 m/s that significantly improves the precision and effect of geomagnetic navigation.
Geomagnetic navigationGeomagnetic model error predictsBP neural networkGeomagnetic filtering
万方数据
维普
