摘要
针对高精度光纤陀螺随机误差,在分析其一般时间序列模型的基础上,提出了一种改进型二阶自回归AR(2)模型,可以在线建立光纤陀螺随机误差模型。根据该模型,采用卡尔曼滤波算法,实现了光纤陀螺惯导系统在对准与导航过程中光纤陀螺随机误差的实时滤波。滤波结果和Allan方差分析证明,光纤陀螺信号中角随机游走、零偏不稳定性、速率随机游走、速率斜坡和量化噪声五项噪声源误差系数都小于滤波前的二分之一,有效减小了光纤陀螺随机误差,提高了光纤陀螺精度。
Based on the general time-sequence model of gyroscope random error, an improved ARMA model was designed, by which the high precise Fiber Optic Gyroscope （FOG） random error model was built on-line. According to this model and the Kaiman filter arithmetic, the FOG random error was filtered in real time in the process of initial alignment and navigation of FOG inertial navigation system. Filtering results and the Allan variance analysis prove that the angle random walk, the bias instability, the rate random walk, the angular rate ramp and the quantification noise of FOG are twice less than those before the FOG random error is filtered. So this modeling and filtering methods can reduce the high-precise FOG error and improve the FOG precision effectively.
出处
《光电工程》
EI
CAS
CSCD
北大核心
2007年第1期1-3,58,共4页
Opto-Electronic Engineering
基金
国家863项目
