组合导航中低成本磁航向系统的神经网络补偿  

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

作　　者：刘育浩[1] 黄新生[1] 徐婉莹[1] 

机构地区：[1]国防科学技术大学机电工程与自动化学院,长沙410073

出　　处：《传感技术学报》2008年第11期1848-1852,共5页Chinese Journal of Sensors and Actuators

基　　金：兵器预研基金项目资助(2020203)

摘　　要：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。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°.

关 键 词：组合导航 磁航向系统 神经网络 卡尔曼滤波 

分 类 号：TP241.61[自动化与计算机技术—检测技术与自动化装置]