基于Kalman滤波的陀螺降噪技术研究

在自适应滑动平均技术基础上针对光纤陀螺的动静态输出设计了混合Kalman滤波算法,首先用窗口分割原始数据,接着用自适应滑动平均法检测窗口内的间断点;没有间断点的窗口内部,使用修正值为M1的Kalman滤波进行信号降噪;窗口内部具有间断点的使用修正值为M2的Kalman滤波进行信号降噪.使用DWT算法、普通Kalman滤波法、混合Kalman滤波对陀螺的动态和静态输出信号进行降噪,仿真结果表明只有混合Kalman滤波同时适用于陀螺的动静态输出.

Research on Gyro Denoising Technology Based on Kalman Filter

A hybrid Kalman filter algorithm is designed based on the self-adaption moving average aimming at the dynamic and static outputs of the fiber-optic gyroscope.First,the original data are segmented by windows and then the discontinuity points in windows are detected by the self-adaption moving average.As for the inner windows without discontinuity point.Kalman filter with the modification value of M₁ is used to reduce signal noise and as for the inner windows with discontinuity points,Kalman filter with the modification value of M₂ is used to reduce signal noise.And as for the dynamic and static outputs of the fiber-optic gyroscope,the signal noise is reduced with methods of DWT algorithm,common Kalman filter and hybrid Kalman filter algorithm.The simulation result shows that nothing but the hybrid Kalman filter algorithm is simultaneously suitable for the dynamic and static outputs of the fiber-optic gyroscope.