组合导航中低成本磁航向系统的神经网络补偿?

根据组合导航的特点,设计了低成本磁航向系统神经网络补偿方法。研究了磁航向系统的误差和补偿技术;在全球定位系统信号良好情况下,以捷联惯导/全球定位组合导航系统的航向信息为参考,使用卡尔曼滤波作为学习算法,建立多层前向神经网络模型补偿磁航向系统。实验结果表明,神经网络补偿方法将磁航向系统的航向角误差由±15°减小到约±1°,取得了明显的效果。

Neural Network Compensation for Low-Cost Magnetic Heading System in Integrated Navigation

According to the characters of integrated navigation, a neural network is designed to compensate the error of a low-cost magnetic heading system(MHS). The error sources of MHS are studied and the compensation methods are analyzed. When the Global Positioning System(GPS) is available, a multilayer feedforward neural network is designed to compensate MHS with the learning method of kalman filter and the reference of strapdown inertial navigation system(SINS)/GPS integrated navigation result. Experiment results show that the neural network can make a significant effect and reduce the heading error of MHS from ?15? to ?1?.