摘要
提出了一种适用于高精度光纤陀螺(FOG)的静态输出信号建模的改进型二阶自回归AR(2)模型,建立了FOG随机误差的实时卡尔曼滤波器,并在FOG捷联惯导系统(SINS)中进行了实际应用。Allan方差分析和实际应用表明,该建模和滤波方法有效减小了高精度FOG误差,在一定程度上提高了FOG SINS的静态初始对准精度,明显降低了导航漂移,提高了导航精度,具有较好的实际应用价值。
A new and improved ARMA model which can be applied in the modeling of high-precise FOG＇s static output signal is presented, and the real time Kalman filter of FOG random drift is built. The improved modeling and filtering method is applied in the FOG strapdown inertial navigation system （SINS）. By the results of the Allan variance analysis and the application, it is showed that this modeling and filtering method can reduce the error of high-precise FOG and improve the static initial alignment precision of FOG SINS at a certain extent. The navigation errors are depressed and the navigation precision is improved.
出处
《中国惯性技术学报》
EI
CSCD
2006年第4期70-72,87,共4页
Journal of Chinese Inertial Technology
基金
国家"863"项目
