Investigation on filter method of FOG drift data based on ARIMA model

XU Fan; MA Guang-fu

doi:10.13873/j.1000-97872007.02.010

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Investigation on filter method of FOG drift data based on ARIMA model

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- Investigation on filter method of FOG drift data based on ARIMA model
- Issue 2, Pages: 31-32+36(2007)
- 作者机构：
  
  1. 哈尔滨工业大学航天学院控制科学与工程系
  2. 哈尔滨工业大学航天学院控制科学与工程系,黑龙江,哈尔滨,150001
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872007.02.010
  CLC： TN965
- Published：2007
- 稿件说明：
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[1]徐帆,马广富.基于ARIMA模型的光纤陀螺随机漂移滤波方法研究[J].传感器与微系统,2007(02):31-32+36.

XU Fan, MA Guang-fu. Investigation on filter method of FOG drift data based on ARIMA model[J]. 2007, (2): 31-32+36.
[1]徐帆,马广富.基于ARIMA模型的光纤陀螺随机漂移滤波方法研究[J].传感器与微系统,2007(02):31-32+36. DOI： 10.13873/j.1000-97872007.02.010.

XU Fan, MA Guang-fu. Investigation on filter method of FOG drift data based on ARIMA model[J]. 2007, (2): 31-32+36. DOI： 10.13873/j.1000-97872007.02.010.

摘要

对光纤陀螺随机漂移输出进行了非平稳性检验

并建立了非平稳求和自回归滑动平均（ARIMA）模型

在此模型的基础上对光纤陀螺随机漂移进行卡尔曼（Kalman）滤波

并对滤波结果进行Allan方差分析。与基于自回归（AR）模型的Kalman滤波结果进行比较

实验结果表明:基于ARIMA模型的Kalman滤波比基于AR模型的Kalman滤波更能减小光纤陀螺的零偏不稳定性和角度随机游走。

Abstract

FOG drift data is validated to be a non-stationary time series and a ARIMA model is established.The FOG drift data is processed by using Kalman filter;and the filter results are analyzed and fitted by Allan variance analyzing method and least squares method.In addition

an AR model is discussed and compared with the ARIMA model.Experimental result shows that ARIMA model based Kalman filter is efficient in reducing the bias instability and angle random walk.

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references

基于AR模型的光纤陀螺建模方法研究 [J]. 陈涛,王新龙,杜宇. 鱼雷技术 . 2005(03)

光纤陀螺漂移的数据分析及建模(英文) [J]. 缪玲娟,张方生,沈军,刘伟. Journal of Beijing Institute of Technology（English Edition） . 2002(01)

光纤陀螺零漂数据滤波方法的研究 [J]. 柳贵福,张树侠. 中国惯性技术学报 . 2001(04)

激光陀螺角随机游走分析方法 [J]. 黄国荣,张宗麟,韩宗虎. 中国惯性技术学报 . 2000(01)

随机过程[M]. 西安交通大学出版社 , 汪荣鑫编, 1987

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