光纤陀螺随机噪声的实时滤波技术  

Filtering Technique on FOG Random Noise and Its Application

作　　者：郑智明[1] 刘建业[1] 赖际舟[1] 钱伟行[1] 祝燕华[1] 

机构地区：[1]南京航空航天大学自动化学院,南京210016

出　　处：《数据采集与处理》2009年第5期671-675,共5页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(60702003)资助项目;航空科学基金(04D52030)资助项目

摘　　要：针对ARMA(Auto-regressive and moving average)模型只能对零均值序列建模的不足,建立了一种适用于中低精度光纤陀螺(Fiber optic gyroscope,FOG)的非零均值信号建模的ARIMA模型,并利用卡尔曼滤波器抑制FOG的随机噪声。Allan方差分析和实际应用结果表明,FOG实测信号通过ARIMA模型的卡尔曼滤波器,各种噪声都得到了有效的抑制。将基于ARIMA模型的卡尔曼滤波误差校正方法应用于转动环境下的FOG输出信号处理,同样得到良好的效果。本文提出的方案扩展了ARIMA滤波算法的应用范围,具有较高的工程应用价值。As an auto-regressive and moving average（ARMA） model can only construct the model of the zero mean sequence, an ARIMA model for modeling the nonzero output of a lowmedium accuracy fiber optic gyroscope （FOG） is established. Then, the random noise of FOG is processed by using Kalman filter, the allan variance analysis and the practical application show that a Kalman filter based on ARIMA model can reject the random noise of FOG. In addition, the Kalman filter based on ARIMA model is applied to FOG signal processing under the rotation condition. Experimental results demonstrate that the performance of the filter is feasible. The method extends the application range of ARIMA model and has the certain value for engineering application.

关 键 词：光纤陀螺 ARIMA模型 卡尔曼滤波 ALLAN方差 

分 类 号：V241.5[航空宇航科学与技术—飞行器设计]