光纤陀螺温度漂移建模与预测

Modeling and Prediction of Fiber Optic Gyro Temperature Drift

温度漂移是光纤陀螺的主要误差之一,它可分为两部分:与系统相关的误差源及环境的随机扰动产生的随机误差项;由温度变化引起的趋势项。提出了一种光纤陀螺温度漂移的改进AR模型和建模方法,先建立随机误差项的AR模型,再在AR模型中引入趋势项。使用实测的光纤陀螺温度漂移数据建模,并验证模型有效性。结果表明,该模型能准确预测不同温度变化情况下陀螺漂移输出,并能用预测值有效补偿漂移误差,补偿后温度漂移减小到补偿前的20%以下。基于Labview开发了可视化软件,该软件在陀螺温度特性的评价与预测方面具有实用价值。

Temperature drift is one of main errors in Fiber Optic Gyro（ FOG） , which can be divided into two terms： a random error term associated with system error and environmental disturbance, and a trend term caused by temperature change. An improved AR model of FOG temperature drift and its modeling method were proposed. Firstly, AR model of the random error term was established, and then the trend term was introduced in the AR model. The measured FOG temperature drift data was used for modeling and verifying the validity of model. Results show that： 1） The proposed model can accurately predict the gyro drift output under different temperature variations, and the predicted value can effectively compensate for the drift error;and 2） The FOG temperature drift after compensation is reduced to lees than 20% of that before compensation.Visual software was developed based on Labview, which is of practical value in assessment and prediction of the gyro temperature characteristics.