基于实时小波的光纤陀螺阈值滤波

Threshold Filtering for Fiber Optic Gyroscope Based on Real-time Wavelet

为补偿姿态测量系统中光纤陀螺(Fiber Optic Gyroscope,FOG)的误差,根据光纤陀螺的静、动态误差在时频域上的分布,介绍了小波滤波的一般理论和方法,分析并比较了阈值和阈值函数的选取;采用数据滑动窗的方法实现了递推运算和实时的数据更新,对窗内数据进行周期对称延拓解决滤波信号的边界问题。仿真实验验证了实时小波阈值滤波在光纤陀螺信号处理中的可行性,得出了不同小波基函数的选取对滤波效果的影响,并验证了采用软硬阈值结合方法实时滤波的优越性,该实时滤波方法不仅提高了陀螺输出的稳定性和使用精度,且对光纤陀螺信号处理具有参考价值。

In order to compensate for the errors of Fiber Optic Gyroscope （FOG） in an attitude measurement system, according to dynamic and static error distributions of FOG in the time and frequency domains, the basic methods of wavelet, analyses are introduced and how to select threshold and threshold function is compared. The algorithm for real-time wavelet threshold filtering with moving window is adopted to de-noise output signals of FOG. Experimental results show the feasibility of the real time wavelet threshold method in FOG signals de-noising. The real-time wavelet de-noising algorithm with combination of soft and hard thresholds has the advantages over single algorithm, the algorithm is able to not only improve the precision and stability of the FOG, but also provide reference value for dealing with the FOG signals.