惯性导航EEMD区间阈值降噪方法

doi:10.11947/j.AGCS.2018.20170391

测绘学报 ›› 2018, Vol. 47 ›› Issue (7): 907-915.doi: 10.11947/j.AGCS.2018.20170391

惯性导航EEMD区间阈值降噪方法

刘韬, 徐爱功, 隋心

辽宁工程技术大学测绘与地理科学学院, 辽宁阜新 123000

收稿日期:2017-07-09 修回日期:2018-01-20 出版日期:2018-07-20 发布日期:2018-07-25
通讯作者: 徐爱功 E-mail:xu_ag@126.com
作者简介:刘韬(1991-),男,硕士,研究方向为UWB/INS组合的室内导航。E-mail:tio_liu@126.com
基金资助:
国家重点研发计划（2016YFC0803102）；辽宁省高等学校创新团队项目（LT2015013）；辽宁省科技厅博士启动基金（201501126）；辽宁省教育厅辽宁省高等学校基本科研项目（LJ2017QL007）

EEMD Interval Threshold De-noising Method for Inertial Navigation

LIU Tao, XU Aigong, SUI Xin

School of Geomatics, Liaoning Technical University, Fuxin 123000, China

Received:2017-07-09 Revised:2018-01-20 Online:2018-07-20 Published:2018-07-25
Supported by:
The National Key Research and Development Program of China (No. 2016YFC0803102);The Colleges and Universities Innovative Research Team Program of Liaoning Province (No. LT2015013);The Doctoral Scientific Research Foundation of Liaoning Province (No. 201501126);The General Science Research Project of Education Bureau of Liaoning Province(No. LJ2017QL007)

摘要/Abstract

摘要： 陀螺随机误差是影响惯性导航系统精度的主要因素。在经验模态分解（EMD）和阈值降噪的基础上，提出一种基于集合经验模态分解（EEMD）的区间阈值的陀螺信号降噪方法。该方法利用EEMD方法将陀螺信号分解多个本征模态函数（IMF）分量和1个残余分量，基于信号和IMF分量的概率密度函数的2范数距离方法剔除纯噪声IMF分量，利用改进的区间阈值降噪方法实现信号的降噪。仿真和实测试验表明，该方法不仅能有效抑制EMD中的模态混叠问题，而且能有效削弱陀螺的随机误差，从而提高惯性导航系统的精度和可靠性。

关键词: 惯性导航系统, 随机误差, 集合经验模态分解, 区间阈值降噪

Abstract: The stochastic error of gyro is the significant factor that affect the precision of inertial navigation system (INS).On the basis of empirical mode decomposition (EMD) method and threshold de-noising method, proposed an ensemble empirical mode decomposition(EEMD) interval threshold de-noising method for gyro signal.The gyro signal is decomposed into several intrinsic mode function(IMF) components and one residual component, then rejecting the IMFs that contain pure noise by the 2-norm measures between the probability density function of IMFs and signal, using an improved interval threshold de-noising method to complete the signal de-noising process.Simulation and real test experiments show that the proposed method can not only effectively restrain the mode mixing phenomenon in EMD, but also effectively reducing the stochastic error of gyro, thus improving the precision and reliability of INS.

Key words: inertial navigation system, stochastic error, ensemble empirical mode decomposition, interval threshold de-noising

中图分类号:

P228

刘韬, 徐爱功, 隋心. 惯性导航EEMD区间阈值降噪方法[J]. 测绘学报, 2018, 47(7): 907-915.

LIU Tao, XU Aigong, SUI Xin. EEMD Interval Threshold De-noising Method for Inertial Navigation[J]. Acta Geodaetica et Cartographica Sinica, 2018, 47(7): 907-915.

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惯性导航EEMD区间阈值降噪方法

EEMD Interval Threshold De-noising Method for Inertial Navigation

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