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自适应FLP滤波在激光陀螺IMU标定中的应用

卢兆兴 房建成 王仕成 李建利 党鹏飞

卢兆兴, 房建成, 王仕成, 等 . 自适应FLP滤波在激光陀螺IMU标定中的应用[J]. 北京麻豆精品秘 国产传媒学报, 2018, 44(6): 1213-1220. doi: 10.13700/j.bh.1001-5965.2017.0462
引用本文: 卢兆兴, 房建成, 王仕成, 等 . 自适应FLP滤波在激光陀螺IMU标定中的应用[J]. 北京麻豆精品秘 国产传媒学报, 2018, 44(6): 1213-1220. doi: 10.13700/j.bh.1001-5965.2017.0462
LU Zhaoxing, FANG Jiancheng, WANG Shicheng, et al. Application of adaptive FLP filter to ring laser gyro IMU calibration[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(6): 1213-1220. doi: 10.13700/j.bh.1001-5965.2017.0462(in Chinese)
Citation: LU Zhaoxing, FANG Jiancheng, WANG Shicheng, et al. Application of adaptive FLP filter to ring laser gyro IMU calibration[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(6): 1213-1220. doi: 10.13700/j.bh.1001-5965.2017.0462(in Chinese)

自适应FLP滤波在激光陀螺IMU标定中的应用

doi: 10.13700/j.bh.1001-5965.2017.0462
基金项目: 

国家自然科学基金 61421063

国家自然科学基金 61473020

国家自然科学基金 61571030

国家自然科学基金 61573040

国家自然科学基金 61722103

国家自然科学基金 61503393

国家“863”计划 2015AA124001

国家“863”计划 2015AA124002

国际(地区)合作与交流项目 61661136007

基础科研项目 YWF-17-BJ-Y-71

详细信息
    作者简介:

    卢兆兴  男, 博士研究生。主要研究方向:惯性导航与组合导航技术

    房建成  男, 博士, 教授, 博士生导师。主要研究方向:惯性导航、组合导航及航天器姿态控制技术

    通讯作者:

    房建成, E-mail:fangjiancheng@cq5520.com

  • 中图分类号: V249.32

Application of adaptive FLP filter to ring laser gyro IMU calibration

Funds: 

National Natural Science Foundation of China 61421063

National Natural Science Foundation of China 61473020

National Natural Science Foundation of China 61571030

National Natural Science Foundation of China 61573040

National Natural Science Foundation of China 61722103

National Natural Science Foundation of China 61503393

National High-tech Research and Development Program of China 2015AA124001

National High-tech Research and Development Program of China 2015AA124002

International (Regional) Cooperation and Communication Project 61661136007

Basic Scientific Research YWF-17-BJ-Y-71

More Information
  • 摘要:

    激光陀螺的高频机抖使得激光陀螺惯性测量单元(IMU)的测量数据包含较大的随机噪声。传统标定方法通过延长测量时间消除对随机噪声的影响,降低了标定效率。提出了应用自适应前向线性预测(FLP)滤波对激光陀螺IMU的标定数据进行降噪,在较小标定数据量情况下提高系统的标定精度。首先通过四方位正反速率标定试验获得原始标定数据;然后通过自适应FLP滤波器对标定数据进行噪声抑制;最后利用降噪后的数据计算标定参数。试验结果表明,该方法能够有效抑制标定数据中的随机噪声,提高信号的信噪比(SNR),从而在标定数据量较小的情况下得到较高精度的标定参数,提升系统的导航精度。

     

  • 图 1  基于LMS的FLP结构

    Figure 1.  FLP structure based on LMS

    图 2  四方位正反速率标定过程示意图

    Figure 2.  Schematic diagram of four-position rotation calibration procedure

    图 3  激光陀螺IMU标定试验系统

    Figure 3.  Experiment system of ring laser gyro IMU calibration

    图 4  降噪前后激光陀螺和加速度计输出数据对比

    Figure 4.  Comparison of ring laser gyro and accelerator output data before and after de-noising

    图 5  降噪前后激光陀螺和加速度计输出数据功率谱分析

    Figure 5.  Power spectrum analysis of ring laser gyro and accelerator output data before and after de-noising

    图 6  车载试验验证系统

    Figure 6.  Vehicle experiment system for verification

    图 7  2套系统的跑车纯惯性导航定位曲线

    Figure 7.  Inertial navigation positioning curves of two systems

    图 8  2套系统的跑车纯惯性导航定位误差曲线

    Figure 8.  Inertial positioning error curves of two systems

    表  1  激光陀螺IMU降噪前标定结果

    Table  1.   Calibration results of ring laser gyro IMU with original calibration data

    参数类型 FLP降噪前结果
    Gbx, Gby, Gbz/((°)·h-1) -0.024 2, -0.234 0, 0.059 0
    Sgx, Sgy, Sgz/(″/^) -0.842 6, 0.842 7, -0.842 8
    Abx, Aby, Abz/(10-4g) 1.399 7, 9.909 8, 22.828 9
    Kax, Kay, Kaz/(10-5g·s/^) -3.386 7, 3.234 7, -3.389 6
    注:(″/^)为角秒每脉冲; (s/^)为秒每脉冲。
    下载: 导出CSV

    表  2  激光陀螺IMU降噪后标定结果

    Table  2.   Calibration results of ring laser gyro IMU with de-noised calibration data

    参数类型 FLP降噪后结果
    Gbx, Gby, Gbz/(°)·h-1) -0.021 1, -0.234 5, 0.077 8
    Sgx, Sgy, Sgz/(″/^) -0.842 6, 0.842 7, -0.842 8
    Abx, Aby, Abz/(10-4g) 1.387 2, 9.909 0, 22.849 1
    Kax, Kay, Kaz/(10-5g·s/^) -3.386 7, 3.234 7, 3.389 7
    下载: 导出CSV

    表  3  1 h车载试验导航定位误差

    Table  3.   1 h positioning error of vehicle experiment

    nmile
    系统编号 导航定位误差
    FLP降噪前 FLP降噪后
    TX-R610-01 0.871 256 0.595 590
    TX-R610-02 0.652 650 0.500 372
    下载: 导出CSV
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出版历程
  • 收稿日期:  2017-07-10
  • 录用日期:  2017-11-17
  • 网络出版日期:  2018-06-20

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