Acta Photonica Sinica, Volume. 48, Issue 12, 1212003(2019)
Modified Adaptive Real-time Filtering Algorithm for MEMS Gyroscope Random Noise
Figures & Tables(13)
Fig. 1. 3DM-GX4-25
Fig. 4. MTi-100 sensor gyro
Fig. 5. Comparison of output data before and after
Fig. 6. Comparison of output data before and after
Fig. 7. Comparison of output data before and after
Fig. 8. Comparison of output data before and after
Table 1. Output mean of two MEMS gyro
View tableView in ArticleTable 1. Output mean of two MEMS gyro
Sensors First set of data Second set of data Third set of data Fourth set of data Mti-100 -0.341 -0.344 -0.346 -0.360 3DM-GX4-25 0.054 0.060 0.063 0.067
Table 2. The traditional method of model identification
View tableView in ArticleTable 2. The traditional method of model identification
Model name AR( p )MA( q )ARMA( p ,q )Self-correlation coefficient function Trailing q step cut-offTrailing Partial correlation coefficient function p -step tailingTrailing Trailing
Table 3. The traditional method of model identification
View tableView in ArticleTable 3. The traditional method of model identification
Parameters X kW kA B ARMA (1, 1) \begin{document}${\left[ {\begin{array}{*{20}{l}} {{y_k}}&k \end{array}} \right]^{\rm{T}}}$\end{document} \begin{document}${\left[ {\begin{array}{*{20}{l}} {{a_k}}&{{a_k} - 1} \end{array}} \right]^{\rm{T}}}$\end{document} \begin{document}$\left[ {\begin{array}{*{20}{l}} {{\varphi _1}}&1\\ 0&1 \end{array}} \right]$\end{document} \begin{document}$\left[ {\begin{array}{*{20}{c}} 1&{{\theta _1}}\\ 0&0 \end{array}} \right]$\end{document} ARMA (2, 1) \begin{document}${\left[ {\begin{array}{*{20}{l}} {{y_k}}&{{y_{k - 1}}}&k \end{array}} \right]^{\rm{T}}}$\end{document} \begin{document}${\left[ {\begin{array}{*{20}{l}} {{a_k}}&{{a_k} - 1} \end{array}} \right]^{\rm{T}}}$\end{document} \begin{document}$\left[ {\begin{array}{*{20}{c}} {{\varphi _1}}&{{\varphi _2}}&1\\ 1&0&0\\ 0&0&1 \end{array}} \right]$\end{document} \begin{document}$\;\left[ {\begin{array}{*{20}{c}} 1&{{\theta _1}}\\ 0&0\\ 0&0 \end{array}} \right]$\end{document}
Table 4. Statistical characteristics of gyro output signal before and after filtering
View tableView in ArticleTable 4. Statistical characteristics of gyro output signal before and after filtering
Sensors Methods Mean Mean variance MTi-100 Original output -0.353 0.078 KF -0.353 0.037 AKF -0.353 0.019 Method in this paper -0.353 0.009 3DM-GX3-25 Original output 0.071 0.197 KF 0.071 0.195 AKF 0.071 0.099 Method in this paper 0.071 0.013
Table 5. Statistical characteristics of gyro output signal before and after filtering
View tableView in ArticleTable 5. Statistical characteristics of gyro output signal before and after filtering
Sensors Methods Mean Mean variance MTi-100 Original output 4.844 0.377 KF 4.844 0.333 AKF 4.844 0.315 Method in this paper 4.844 0.275 3DM-GX3-25 Original output 5.092 0.323 KF 5.092 0.321 AKF 5.092 0.317 Method in this paper 5.092 0.269
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Jun FU, Hong-xiang HAN. Modified Adaptive Real-time Filtering Algorithm for MEMS Gyroscope Random Noise[J]. Acta Photonica Sinica, 2019, 48(12): 1212003
Paper Information
Received: May. 7, 2019
Accepted: Sep. 3, 2019
Published Online: Mar. 17, 2020
The Author Email: HAN Hong-xiang (17607114660@163.com)
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