A Gyroscope Signal Denoising Method Based on Empirical Mode Decomposition and Signal Reconstruction

To suppress the random drift error of a gyroscope signal, this paper proposes a novel denoising method, which is based on processing the intrinsic mode functions (IMFs) obtained by empirical mode decomposition (EMD). Considering that a gyroscope signal contains colored noise in addition to Gaussian...

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Bibliographic Details
Published in:Sensors (Basel, Switzerland) Switzerland), 2019-11, Vol.19 (23), p.5064
Main Authors: Liu, Chenchen, Yang, Zhiqiang, Shi, Zhen, Ma, Ji, Cao, Jian
Format: Article
Language:English
Subjects:
Accuracy
colored noise
Decomposition
empirical mode decomposition
Fractals
gyroscope
hausdorff distance
interval threshold
Methods
Metric space
Neurosciences
Noise
Noise reduction
Random noise
Sensors
signal denoising
Signal processing
Signal reconstruction
Wavelet transforms
White noise
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Summary:To suppress the random drift error of a gyroscope signal, this paper proposes a novel denoising method, which is based on processing the intrinsic mode functions (IMFs) obtained by empirical mode decomposition (EMD). Considering that a gyroscope signal contains colored noise in addition to Gaussian white noise, fractal Gaussian noise (FGN) was introduced to quantify the noise in the gyroscope data. The proposed denoising method combines the FGN energy model and the modified method of Hausdorff distance (HD) to adaptively divide the IMFs into three categories (pure noise, pure information, and mixed components of noise and information). Then, the information IMFs and the mixed components after thresholding were selected to give the optimal signal reconstruction. Static and dynamic signal tests of the fiber optic gyroscope (FOG) were carried out to illustrate the performance of the proposed method, and compared with other traditional EMD denoising methods, such as the Euclidean norm measure method (EMD-l2-norm) and the sliding average filtering method (EMD-SA). The results of the analysis of both the static and dynamic signal tests indicate the effectiveness of the proposed method.
ISSN:1424-8220
1424-8220
DOI:10.3390/s19235064