IUKF neural network modeling for FOG temperature drift

• 作 者: Feng Zha Jiangning Xu Jingshu
• 机 构: DepartmentofNavigationEngineering
• 出 处: 系统工程与电子技术：英文版
• 发表日期: 2013年5期
• 关键词: 神经网络建模 温度漂移 光纤陀螺 无迹卡尔曼滤波 状态矢量 迭代计算 神经网络优化 漂移模型 fiber optic gyro （FOG） temperatu
• 基金项目: This work was supported by the National Natural Science Foundation of China （61100184, 40900018）, the National Key Scientific Instrument and Equipment Development Project （2011YQ12004502）, the Researc

A novel neural network based on iterated unscented Kalman filter(IUKF) algorithm is established to model and compensate for the fiber optic gyro(FOG) bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and t