@ARTICLE{Rong_Hailong_A_2023,
 author={Rong, Hailong and Jin, Tianlei and Wang, Hao and Wu, Xiaohui and Zou, Ling},
 volume={vol. 30},
 number={No 4},
 journal={Metrology and Measurement Systems},
 pages={755-772},
 howpublished={online},
 year={2023},
 publisher={Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation},
 abstract={To reduce the random error of microelectromechanical system (MEMS) gyroscope, a hybrid method combining improved empirical mode decomposition (EMD) and least squares algorithm (LS) is proposed. Firstly, based on the multiple screening mechanism, intrinsic mode functions (IMFs) from the first decomposition are divided into noise IMFs, strong noise mixed IMFs, weak noise mixed IMFs and signal IMFs. Secondly, according to their characteristics, they are processed again. IMFs from the second decomposition are divided into noise IMFs and signal IMFs. Finally, useful signal is gathered to obtain the final denoising signal. Compared with some other denoising methods proposed in recent years, the experimental results show that the proposed method has obvious advantages in suppressing random error, greatly improving the signal quality and improving the accuracy of inertial navigation.},
 type={Article},
 title={A hybrid denoising method for gyroscopes based on multiple screening},
 URL={http://www.journals.pan.pl/Content/130312/art10_int.pdf},
 doi={10.24425/mms.2023.147962},
 keywords={micro electromechanical system, multiple screening mechanism, empirical mode decomposition},
}