基于EMD-LWT的光纤陀螺阈值去噪

戴邵武; 郑百东; 戴洪德; 聂子健

doi:doi:10.12086/oee.2019.180333

光电工程, 2019, 46 (5): 180333, 网络出版: 2019-07-25

基于EMD-LWT的光纤陀螺阈值去噪

Fiber optic gyroscope threshold denoising based on EMD-LWT

论文大纲

戴邵武郑百东 ^*戴洪德聂子健

作者单位

海军航空大学岸防兵学院，山东烟台 264001

光纤陀螺小波分析滤波 fiber optic gyroscope wavelet analysis EMD-LWT EMD-LWT filtering

摘要

光纤陀螺 (FOG)温度漂移数据常常淹没在各种噪声背景中，直接补偿建模漂移信号十分困难，为了更好地消除混杂在光纤陀螺温漂数据中的噪声，提出了一种经验模态分解(EMD)和提升小波变换(LWT)相结合的 EMD-LWT滤波方法对光纤陀螺输出信号进行预处理。首先对光纤陀螺含噪信号进行 EMD分解，根据信息熵值判断本征模态函数(IMF)的噪声项和混合模态项，然后对噪声项进行 LWT去噪，混合模态项进行小波分析去噪。对某干涉型 FOG进行静态测试获得陀螺漂移数据，本文提出方法与小波变换和提升小波变换滤波方法进行了对比分析。实测数据计算结果表明，本文提出的 EMD-LWT滤波算法具有最好的滤波效果，经处理后重构信号的均方根误差 (RMSE)下降了 63%，有效地滤除了 FOG输出中的噪声。

Abstract

Fiber optic gyroscope (FOG) drift data is often submerged in various noises backgrounds. It is very difficult to compensate for modeling drift signals directly. In order to better eliminate the noise mixed in the FOG temperature drift data, a hybrid EMD-LWT filtering algorithm based on empirical mode decomposition (EMD) and lifting wavelet transform (LWT) threshold denoising was proposed for gyro signals preprocessing. Firstly, the noise signal of fiber optic gyro is decomposed by EMD, and the noise term and the mixed modal term of the intrinsic mode functions (IMF) are judged according to the information entropy. Then the noise term is de-noised by LWT and the mixed modal term is denoised by wavelet transform (WT). A static test was performed on an interferential FOG to verify the effective-ness of the algorithm and compared with WT and LWT. The experimental results show that the proposed EMD-LWT filtering algorithm has better filtering effect. After processing, the root mean square error (RMSE) of the recon-structed signal is reduced by 63%, which effectively removes the noise in the FOG output.

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戴邵武, 郑百东, 戴洪德, 聂子健. 基于EMD-LWT的光纤陀螺阈值去噪[J]. 光电工程, 2019, 46(5): 180333. Dai Shaowu, Zheng Baidong, Dai Hongde, Nie Zijian. Fiber optic gyroscope threshold denoising based on EMD-LWT[J]. Opto-Electronic Engineering, 2019, 46(5): 180333.

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