基于动态Allan方差的光纤陀螺随机误差分析及算法改进

Research on Random Errors of Fiber Optic Gyro Based on Dynamic Allan Variance and Algorithm Improvement

为了全面了解光纤陀螺(FOG)各项随机误差随时间的变化特性,利用动态Allan方差(DAVAR)方法对光纤陀螺输出信号进行了分析研究。结果表明,与经典Allan方差对光纤陀螺随机误差的分析相比较,DAVAR不仅能准确地评估光纤陀螺各项误差,而且能够直观地反映光纤陀螺各项误差随时间变化的稳定性;由于DAVAR需要估计出陀螺信号各个时间点的Allan方差,因此其具有随着分析数据量增大、运算耗时急剧增加的缺点。为此提出了一种基于选择相关时间序列t的改进型快速DAVAR的计算方法。实验证明,在不影响DAVAR运算结果的前提下,改进型快速DAVAR算法在大数据量分析时有效提高了运算效率。

In order to comprehensively understand the characteristics of random drift of fiber optic gyro（FOG） varying with time, the characteristics of the random error terms of FOG utilizing the dynamic Allan variance（DAVAR） method are studied. The results show that, the DAVAR not only can accurately assess each error of FOG, but also can directly reflect the error stability of FOG. As the DAVAR needs to estimate the Allan variances at all time points, the computational time of the DAVAR grows very quickly with the increase of the analyzed time series. In order to solve the problem, a improved fast DAVAR algorithm based on the choice of relevant time t for the computation of the DAVAR is proposed. The results show that the improved fast DAVAR algorithm dramatically reduces the computational time without affecting operation results.