摘要
针对卫星导航定位基准站高程时间序列受各类噪声干扰导致难以提取有用信号的问题,该文结合互补集合经验模态分解方法(CEEMD)算法和时移多尺度排列熵(TSMPE),提出了一种CEEMD-TSMPE的高程时间序列降噪方法。该方法利用噪声与信号各自的本征模态函数(IMF)分量的时移多尺度排列熵值存在差异的特点将其区分为噪声分量、信噪混合分量、信号分量;利用软阈值法对混合分量进行降噪;将混合分量的降噪结果与信号分量进行重构。采用BJFS站与JOEN站2000—2020年的高程时间序列和仿真信号数据进行实验分析。实验结果表明:该文提出的降噪方法可以根据信噪自身性质有效界定信噪分量并完成降噪,可为进一步研究提供可靠的数据支持。
Aiming at the problem that it is difficult to extract useful signals from the elevation time series of satellite navigation and positioning reference stations disturbed by various noises,this paper is based on the complementary ensemble empirical mode decomposition(CEEMD)algorithm and time shifted multi-scale permutation entropy,(TSMPE)proposes a method for noise reduction of elevation time series based on ceemd-tsmpe.Firstly,according to the difference of the time-shift multi-scale arrangement entropy of the intrinsic mode function(IMF)components of noise and signal,it is divided into noise component,signal-to-noise mixed component and signal component.Secondly,the soft threshold method is used to reduce the noise of the mixed component.Finally,the noise reduction results of the mixed component and the signal component are reconstructed.The elevation time series and simulation signal data of BJFS station and JOEN station from 2000 to 2020 are used for experimental analysis.The experimental results show that the noise reduction method proposed in this paper can effectively define the signal-to-noise component and complete the noise reduction according to the characteristics of signal-to-noise,which provides more reliable data support for further research.
作者
王佩贤
李浩然
兰文琦
张恒璟
金泽林
WANG Peixian;LI Haoran;LAN Wenqi;ZHANG Hengjing;JIN Zelin(School of Surveying,Mapping and Geography,Liaoning University of Technology,Fuxin,Liaoning 123000,China;China Energy Construction Group Liaoning Electric Power Survey and Design Institute Co.,Ltd.,Shenyang 110000,China)
出处
《测绘科学》
CSCD
北大核心
2022年第5期33-40,共8页
Science of Surveying and Mapping
基金
高分对地观测系统重大专项(GF-7卫星高程基准转换模型构建与应用技术)
2017年辽宁省教育厅青年项目(LJ2017QL008)
高分遥感测绘应用示范系统(一期)项目
中国测绘科学研究院基本科研业务费项目(AR1918)
