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超流体陀螺相位波动噪声自适应抵消系统分析

赵玉龙 沈怀荣 任元

赵玉龙, 沈怀荣, 任元等 . 超流体陀螺相位波动噪声自适应抵消系统分析[J]. 北京航空航天大学学报, 2018, 44(3): 508-515. doi: 10.13700/j.bh.1001-5965.2017.0199
引用本文: 赵玉龙, 沈怀荣, 任元等 . 超流体陀螺相位波动噪声自适应抵消系统分析[J]. 北京航空航天大学学报, 2018, 44(3): 508-515. doi: 10.13700/j.bh.1001-5965.2017.0199
ZHAO Yulong, SHEN Huairong, REN Yuanet al. Phase fluctuation noise adaptive cancellation system of superfluid gyroscope[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(3): 508-515. doi: 10.13700/j.bh.1001-5965.2017.0199(in Chinese)
Citation: ZHAO Yulong, SHEN Huairong, REN Yuanet al. Phase fluctuation noise adaptive cancellation system of superfluid gyroscope[J]. Journal of Beijing University of Aeronautics and Astronautics, 2018, 44(3): 508-515. doi: 10.13700/j.bh.1001-5965.2017.0199(in Chinese)

超流体陀螺相位波动噪声自适应抵消系统分析

doi: 10.13700/j.bh.1001-5965.2017.0199
基金项目: 

国家自然科学基金 51475472

国家“863”计划 2015AA8018038C

详细信息
    作者简介:

    赵玉龙  男,博士研究生。主要研究方向:先进惯性测量与控制技术

    任元  男,博士,副教授。主要研究方向:先进惯性测量与控制技术

    通讯作者:

    任元, E-mail: renyuan_823@aliyun.com

  • 中图分类号: V448.2

Phase fluctuation noise adaptive cancellation system of superfluid gyroscope

Funds: 

National Natural Science Foundation of China 51475472

National High-tech Research and Development Program of China 2015AA8018038C

More Information
  • 摘要:

    针对超流体陀螺相位波动噪声影响陀螺角速度检测精度的问题,提出了一种基于递推最小二乘(RLS)算法的陀螺自适应噪声抵消系统。首先,建立了超流体陀螺的相位检测模型,得到了陀螺输出薄膜幅值和相位的关系。其次,考虑热运动的影响,建立了相位波动噪声的等效输入角速度模型,探索了陀螺参数对角速度噪声的影响,得到了陀螺角速度噪声幅值范围。在此基础上,考虑该角速度噪声与输入角速度的互不相关性,将超流体陀螺薄膜幅值解算输出的混合角速度信息作为抵消系统的期望输入,将相位波动噪声引起的角速度噪声作为RLS自适应滤波器的参考输入,通过自适应调节参数使得RLS自适应滤波器的输出与混合角速度信息的噪声部分相抵消。通过与最小均方(LMS)算法仿真对比表明,在大角速度、大噪声情况下,该抵消系统能够有效消除陀螺混合角速度信息中的噪声成分,且具有较快的收敛速度和较好的稳定性。

     

  • 图 1  超流体陀螺示意图

    Figure 1.  Schematic of superfluid gyroscope

    图 2  噪声自适应抵消系统示意图

    Figure 2.  Schematic of noise adaptive cancellation system

    图 3  横向滤波器结构

    Figure 3.  Structure of transversal filter

    图 4  角速度噪声变化曲面

    Figure 4.  Change surface of angular velocity noise

    图 5  背景信息的时域和频域特性

    Figure 5.  Time domain and frequency domain characteristics of background information

    图 6  基于RLS算法的噪声抑制效果

    Figure 6.  Noise suppression effect based on RLS algorithm

    图 7  3种算法的噪声抑制效果

    Figure 7.  Noise suppression effect of three algorithms

    图 8  3种算法的输出误差平方

    Figure 8.  Square of output error of three algorithms

    图 9  3种算法的均方误差

    Figure 9.  Mean square error of three algorithms

    图 10  大角速度、大噪声时3种算法的均方误差

    Figure 10.  Mean square error of three algorithmswhen angular velocity and noise are large

    表  1  超流体陀螺的主要参数

    Table  1.   Main parameters of superfluid gyroscope

    参数 数值
    柔性薄膜面积/cm2 0.5
    微孔数目 4 225
    超流体密度/(kg·m-3) 3
    陀螺的感应面积/cm2 10
    临界流量/(kg·s-1) 5.6×10-12
    下载: 导出CSV

    表  2  输入信噪比为3 dB时的相关量化指标

    Table  2.   Relevant quantitative indicators when input signal to noise ratio is 3 dB

    算法 均方误差/(10-12rad2·s-2) 输出信噪比/dB 100次迭代运算耗时/s
    RLS 1 16.43 5.124
    LMS 1 12.03 2.552
    NLMS 1 12.39 3.414
    下载: 导出CSV

    表  3  输入信噪比为-3 dB时的相关量化指标

    Table  3.   Relevant quantitative indicators when input signal to noise ratio is -3 dB

    算法 均方误差/(10-12rad2·s-2) 输出信噪比/dB 100次迭代运算耗时/s
    RLS 4 16.31 5.281
    LMS 4 9.29 2.474
    NLMS 4 9.48 3.282
    下载: 导出CSV

    表  4  大角速度、大噪声时的相关量化指标

    Table  4.   Relevant quantitative indicators when angular velocity and noise are large

    算法 均方误差/(10-12rad2·s-2) 输入信噪比/dB 输出信噪比/dB 100次迭代运算耗时/s
    RLS 16 3 16.44 5.304
    LMS 16 3 4.52 2.492
    NLMS 16 3 10.48 3.293
    下载: 导出CSV
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出版历程
  • 收稿日期:  2017-04-05
  • 录用日期:  2017-06-09
  • 刊出日期:  2018-03-20

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