随机漂移是影响光纤陀螺(FOG)导航精度的重要因素,建立数学模型并进行补偿是一种减小其影响的简易而有效的方法。首先通过分析FOG输出序列的自相关函数,得出其时间相关性呈较弱现象,继而分别使用Yule-Walker算法及最小二乘法求出线性AR及非线性AR(NAR)模型参数,最后比较各模型的滤波效果以确定要采用的模型及其阶数,并进行模型适用性检验。验证结果表明,AR(1)与NAR(1)模型均适合FOG随机漂移的建模及实时滤波,且能较好改善其零偏稳定性。

The random drift is one of the most significant factors that can affect the navigation precision of fiber of gyroscope (FOG). At first, it can be found that its time-relativity was weak based on the auto-related-function analysis of FOG's output series. Then the parameters of linear AR-model and nonlinear AR-model were worked out by the function of Yule-Walker and LMS. At last, the models and their most suitable orders were chosen by both the filtered effect and applicable test. The results indicate that both AR(1)-model and NAR(1)-model are suitable for the FOG's random drift modeling and real-time filtering, and can improve the zero bias's stability obviously.