关键词: BP神经网络, 导航定位, 卡尔曼滤波, 自适应能力

Abstract: The noise of GPS navigation position system has the character of apriority，and the optimal estimation carried out by Kalman filter need to establish accurate system model and observation model.These lead to the low accuracy of the standard Kalman filter.In order to improve filtering accuracy，arithmetic for dynamic GPS Kalman filtering modified by neural network is proposed.Two BP neural network is used to correct the standard Kalman filter in the time update predict part and measure update part.The method not only considers the random interference with the dynamic change，but also utilizes neural network’s capability of self-taught and self-adapted.The simulation results show that the algorithm is better than that of standard Kalman filtering.

Key words: BP neural network, navigation orientation, kalman filtering, capability of self-adapted