Modeling and simulation of FOG random drift based on Allan variance
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摘要: 随机漂移是影响光纤陀螺精度的主要因素之一，建立陀螺随机漂移模型以便在滤波时加以修正是提高系统精度的有效方法。针对传统随机漂移模型建模耗时长、过敏感等问题，提出基于Allan方差的光纤陀螺随机漂移模型。通过各噪声项的功率谱密度函数推导出随机微分方程，用Allan方差分析出光纤陀螺各噪声项量化参数，将量化参数代入以单位白噪声驱动的随机微分方程，得到随机漂移模型。实验结果表明，该模型拟合出的随机漂移单项噪声误差不超过8.6％，远低于传统模型产生的单项噪声误差58.3％，是一种有效的光纤陀螺随机漂移建模方法。Abstract: Random drift is one of the main errors in fiber optical gyroscope (FOG). Modeling and revising random drift is an efficient method to improve system accuracy in filtering. Based on Allan variance, the differential equation model(DEM) of random drift is required to solve the shortages of traditional models which are time-consuming and over sensitive. In this paper, the power spectrum density (PSD) function was exploited to figure out the stochastic differential equation (SDE) of every noise. By using Allan variance to calculate the parameter of every noise and substituting the parameter in SDE which was driven by white noise, the random drift model was established. Experiment result illustrates that, the fitting error of random drift is no more than 8.6%，far lower than the traditional one of 58.3％. It is an effective method to build error model of random drift for FOG.
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