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一种惯性传感器混叠干扰信号分离方法 被引量:2

Inertial sensor aliasing interference signal separation method
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摘要 光电跟踪系统中,在惯性传感器混叠信号中分离出各种干扰进行单独抑制具有重要意义,针对目前不同干扰信号单独分离所存在的困难,提出对混叠干扰信号进行小波滤波,得到低频干扰信号,再对滤波后的信号进行集合经验模态分解,得到多个信号分量并利用主成分分析进行降维,最后通过盲源分离算法得到高频混叠信号中的不同频率段干扰信号。仿真结果表明该算法分离出的信号频谱不混叠并且与相对应源信号的相关系数高,分别为0.998 2、0.944 2、0.913 7。真实传感器数据实验证明,算法得到的频率为0.1Hz、8Hz、16Hz、33Hz的信号频谱不混叠,实现了混叠信号不同频段干扰信号的单独分离。 In electro-optical tracking systems,it is of great significance to separate out various interference in the aliasing signal of inertial sensor to suppress them individually.Aiming at the difficulty of separate separation of different interference signals,wavelet filtering is applied to the aliased interference signals to obtain low-frequency interference signals,and then the filtered signal is subjected to ensemble empirical mode decomposition to obtain multiple signal components and the principal component analysis is used to reduce the dimension.Finally,the blind source separation algorithm is used to process the signals to obtain different frequency segment interference signals in the high-frequency alias signals.Simulation results show that the signals separated by the algorithm are not aliased and their correlation coefficients with the corresponding source signals are high,which are 0.998 2,0.944 2,and 0.913 7,respectively.Experiments on real sensor data show that the frequency spectrum of the signal obtained by the algorithm is 0.1 Hz,8 Hz,16 Hz and 33 Hz without aliasing,which realizes separate separation of the interference signals of different frequency bands of the aliased signal.
作者 胡亭亭 包启亮 夏运霞 Hu Tingting;Bao Qiliang;Xia Yunxia(Key Laboratory of Optical Engineering,Chinese Academy of Sciences,Chengdu 610209,China)
出处 《国外电子测量技术》 2018年第11期66-71,共6页 Foreign Electronic Measurement Technology
关键词 惯性传感器 小波滤波 主成分分析 经验模态分解 盲源分离 inertial sensors wavelet filtering principal component analysis empirical mode decomposition (EEMD) blind source separation
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  • 1李杨,胡柏青,覃方君,查峰.光纤陀螺信号的解耦自适应Kalman滤波降噪方法[J].中国惯性技术学报,2014,12(2):260-264. 被引量:11
  • 2曾庆化,黄磊,刘建业,陈磊江,顾姗姗.基于ARMA模型的光纤陀螺随机噪声滤波方法[J].中国惯性技术学报,2015,23(1):120-124. 被引量:17
  • 3胡昌华 张军波.基于MATLAB的系统分析与设计—小波分析[M].西安:西安电子科大出版社,1998.3-69.
  • 4Rogers R M. Velocity-plus-rate matching for improved tactical weapon rapid transfer alignment[Z]. AIAA Guidance, Navigation and Control Conference,[s.l.], 1991.
  • 5Kain J E, Cloutier J R. Rapid transfer alignment for tactical weapon applications[R]. AIAA-89-3581,1989.
  • 6Narotham S R. Transfer orbit stage gyrocompass alignment algorithm twist and sway environment for mars oberver mission on commercial titan[J]. IEEE AES Magazine, 1992(2):3-7.
  • 7Kownacki C. Optimization approach to adapt Kalman filters for the real-time application of accelerometer and gyroscope signals filtering[ J ]. Digital Signal Processing,2011,21 ( 1 ).
  • 8Allan D W, Barnes J A. A modified "Allan variance" with increased oscillator characterization ability[ C]//35th Annu- al Frequency Control Symposium. 1981:470 -475.
  • 9Yang Y X. Adaptively robust Kalman filters with applications in navigation [ J ]. Sciences of Geodesy-l,2010:49 - 82 .
  • 10Zurbenko I, Porter P S, Gui R, et al. Detecting discontinuities in time series of upper-air data : development and demonstra- tion of an adaptive filter technique [ J ]. Journal of Chmate, 2009,9(12) :3548 - 3560.

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