Denoising of MEMS Gyroscope Based on Improved Wavelet Transform

Guangwu CHEN; Xiaobo LIU; Di WANG; Shede LIU

doi:10.11999/JEIT180590

Volume 41 Issue 5

Apr. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(5): 1025-1031

Guangwu CHEN, Xiaobo LIU, Di WANG, Shede LIU. Denoising of MEMS Gyroscope Based on Improved Wavelet Transform[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1025-1031. doi: 10.11999/JEIT180590

Citation:

Guangwu CHEN, Xiaobo LIU, Di WANG, Shede LIU. Denoising of MEMS Gyroscope Based on Improved Wavelet Transform[J]. Journal of Electronics & Information Technology, 2019, 41(5): 1025-1031. doi: 10.11999/JEIT180590

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Denoising of MEMS Gyroscope Based on Improved Wavelet Transform

doi: 10.11999/JEIT180590

1.
Automatic Control Research Institute, Lanzhou Jiaotong University, Lanzhou 730070, China
2.
Gansu Provincial Key Laboratory of Traffic Information Engineering and Control, Lanzhou 730070, China

Funds: The National Natural Science Foundation of China (61863024, 71761023), The Gansu Basic Research Innovation Group Program (1606RJIA327), The Gansu Natural Science Foundation (18JR3RA107 1610RJYA034), Granted by Gansu Provincial Higher Education Research Project (2018C-11), The Gansu Province Science and Technology Plan Funding (18CX3ZA004)

Received Date: 2018-06-13
Rev Recd Date: 2018-12-25

Available Online: 2019-01-04

Publish Date: 2019-05-01

Abstract

Abstract

In order to improve the measurement accuracy of Micro Electro Mechanical Systems (MEMS) gyroscopes, the influence of measurement noise on them is suppressed. The error characteristics of a certain type of MEMS gyroscope are analyzed. A strong tracking self-feedback model based on Recursive Least Square (RLS) multiple wavelet decomposition reconstruction is proposed to establish a new soft threshold function. Since the model processed data has partial singular values, an improved median filtering algorithm is proposed. For the problem of gyro zero-bias noise, a zero-bias stability suppression algorithm is proposed. In this paper, the algorithm model is described in detail, and the experimental data of the train attitude measurement system in a project research are applied to the algorithm model. The test experiments are divided into static and dynamic groups. The results show that the algorithm reduces the noise in the signal, suppresses effectively the random drift of the MEMS gyroscope and improves the accuracy of the attitude calculation. The feasibility and effectiveness of this method are affirmed to remove the signal noise of the gyroscope output and improve the accuracy of the use.
- MEMS gyroscope,
- Wavelet decomposition,
- Attitude estimation

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References(20)

References

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