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Error estimation of airborne strapdown inertial navigation system based on neural network

机译:基于神经网络的机载捷联惯导系统误差估计

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Strapdown Inertial Navigation System play an important role in many different kinds of applications. As the accuracy of which is deeply influenced by the sensors precision, so the system error propagation should be addressed. Based on the airborne vehicle characteristics, a method based on neural network is proposed to estimate the attitude, velocity and position error of system. The simulation experiment results validate the algorithm in estimate some kind of system errors is better than the traditional method based on Kalman filter model.
机译:截带惯性导航系统在许多不同类型的应用中起着重要作用。作为对传感器精度深度影响的准确性,因此应解决系统错误传播。基于机载车辆特性,提出了一种基于神经网络的方法来估计系统的姿态,速度和位置误差。仿真实验结果验证估计算法某种系统错误优于基于卡尔曼滤波器模型的传统方法。

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