基于RBF神经网络的光纤陀螺温度补偿  

Temperature Compensation for FOG Based on RBF Neural Networks

作　　者：杨国梁[1] 徐烨烽[1] 徐海刚[1] 

机构地区：[1]北京航空航天大学仪器科学与光电工程学院,北京100083

出　　处：《压电与声光》2010年第3期361-363,共3页Piezoelectrics & Acoustooptics

摘　　要：针对某型捷联惯导系统中光纤陀螺仪的输出信号随温度漂移严重的问题,使用径向基函数(RBF)神经网络建立温度补偿模型。神经网络的结构为输入层和输出层各有一个节点,中间隐层含有4个节点,隐层节点的聚类中心均匀分布在温度的变化范围之内。实验结果表明,该方法可有效地将光纤陀螺仪中的温漂误差减小1个数量级以上,补偿效果明显。In the view of serious temperature excursion of the fiber optic gyroscope（FOG） in a strapdown inertial navigation system,a temperature compensation model is established by using RBF neural network.The input layout and output layout of the neural network have one node separately,the middle layout has four nodes,and the aggregation center points of the nodes in the middle layout are scattered evenly among the changing area of the temperature.It is proved by the experiment that this method could reduce the gyro′s temperature excursion at least 1 order of magnitude in comparison with the traditional method.The effect of compensation is distinct.

关 键 词：光纤陀螺 径向基函数(RBF)神经网络 温度补偿 

分 类 号：TN915[电子电信—通信与信息系统] V241.5[电子电信—信息与通信工程]