利用神经网络预测的GPS/SINS组合导航系统算法研究

GPS/SINS Integrated Navigation Algorithm Based on Neural Network Prediction

  • 摘要: 提出了一种基于神经网络预测的GPS/SINS组合导航系统算法。GPS信号可用时,该算法分别将惯性传感器的输出以及卡尔曼滤波器的输出信息作为神经网络的输入及理想输出信息,并进行在线训练;当GPS信息失锁时,利用已经训练好的神经网络预测各导航参数误差,并校正SINS。地面静态实验与动态跑车实验结果证明了该方法的可行性与有效性。

     

    Abstract: We put forward a GPS/SINS integrated navigation algorithm based on neural network(NN) prediction.When GPS signal is available,this method uses the outputs of inertial sensors and the outputs of Kalman filter as the inputs and ideal outputs of NN respectively,and the NN is trained on-line.During GPS signal outage,the trained NN is used to predict the navigation parameter error to correct SINS.The ground static and dynamic car experimental results show the reliability and effectiveness of this method.

     

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