基于自适应窗长的光纤陀螺随机误差实时分析方法

Real-Time Analysis Method for Stochastic Error of Fiber Optic Gyroscope Based on Adaptive Window Length

动态Allan方差是分析光纤陀螺随机误差的一种新方法。针对其采用固定窗长的窗函数截断信号,导致动态跟踪效果与方差估计值的置信度不能兼顾的问题,提出了一种基于峭度自动调节窗长的改进算法。算法引入峭度参数表征陀螺输出信号的平稳程度,以滑动窗内数据的峭度值为变量构造窗长截取函数,应用窗长函数根据短时信号的稳定程度自动确定截断窗窗长,并用其来截取随机信号进而进行Allan方差估计及误差系数实时辨识和提取,同时将方差估计值和误差系数时间曲线分别绘制在三维或二维图上。对仿真和实测数据分析结果表明:新算法既能在平稳性好的数据段保持较高的置信度,又能在发生动态变化时及时跟踪信号,可以更好地对光纤陀螺的随机误差系数进行实时在线提取和分析。

The dynamic Allan variance （DAVAR） is a new method for analyzing stochastic error of gyroscope. However, it has difficulty in making a good tradeoff between tracking capabilities and variance reduction due to the window with fixed length. An improved algorithm based on kurtosis and time-variant window is proposed to quickly track variations in the signal and obtain a low variance of the estimate. The kurtosis is introduced into analysis of gyroscope output, and the window length function to truncate signal is built by taking kurtosis as variables,which can make window length change with the non-stationary of the signal automatically. Then the length of truncation window is estimated according to the function, the values of Allan variance is obtained in the windows, and the error coefficients can also be identified and extracted at the same time. The above data are expressed by three or two-dimensional to describe the dynamic characteristics of gyro. Simulation and experimental data analysis results show that the proposed algorithm can track the non-stationary of gyroscope more effectively and obtain a good confidence in stationary random process, and the method can be more effective for the extraction and identification of stochastic error coefficients.