Laser & Optoelectronics Progress, Volume. 57, Issue 15, 150601(2020)
De-Noising Method for Gyroscope Signal Based on Improved Ensemble Empirical Mode Decomposition
In order to suppress the nonlinear and nonstationary noise of a gyroscope, this paper proposes an improved de-noising method called EEMD-M based on ensemble empirical mode decomposition (EEMD). First, the information and noise dominated intrinsic mode function (IMF) components are obtained by EEMD threshold filtering. Then, EEMD is applied to the discarded IMF components in the first threshold filtering to extract the signal detail. The scaling index of each IMF component is defined by the detrended fluctuation analysis (DFA) method, and the useful components in the secondary decomposition are further extracted. Finally, the useful IMF components obtained after the two decompositions are reconstructed to obtain a de-noised signal. In order to verify the effectiveness of the proposed EEMD-M, the noise reduction experiments for the measured data are carried out. The results show that the proposed algorithm is superior to the empirical mode decomposition (EMD) de-noising method, DFA-EMD de-noising method, EEMD de-noising method, and wavelet analysis method. The mean square error of the measured data decreases by 82.9%, and the random drift is significantly suppressed, which verifies the feasibility and superiority of the proposed EEMD-M and improves the stability and reliability of the micro electromechanical system gyroscope in optical image processing.
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Qian Wu, Yu Liu. De-Noising Method for Gyroscope Signal Based on Improved Ensemble Empirical Mode Decomposition[J]. Laser & Optoelectronics Progress, 2020, 57(15): 150601
Category: Fiber Optics and Optical Communications
Received: Oct. 18, 2019
Accepted: Nov. 25, 2019
Published Online: Aug. 4, 2020
The Author Email: Liu Yu (liuyu@tju.edu.cn)