Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion
As an important inertial sensor, the gyroscope is mainly used to measure angular velocity in inertial space. However, due to the influence of semiconductor thermal noise and electromagnetic interference, the output of the gyroscope has a certain random noise and drift, which affects the accuracy of...
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doaj-2995429397e0454fa9076e41801779c72020-11-25T01:57:09ZengMDPI AGSensors1424-82202019-08-011916355210.3390/s19163552s19163552Research on Filtering Algorithm of MEMS Gyroscope Based on Information FusionHui Guo0Huajie Hong1College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, ChinaCollege of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, ChinaAs an important inertial sensor, the gyroscope is mainly used to measure angular velocity in inertial space. However, due to the influence of semiconductor thermal noise and electromagnetic interference, the output of the gyroscope has a certain random noise and drift, which affects the accuracy of the detected angular velocity signal, thus interfering with the accuracy of the stability of the whole system. In order to reduce the noise and compensate for the drift of the MEMS (Micro Electromechanical System) gyroscope during usage, this paper proposes a Kalman filtering method based on information fusion, which uses the MEMS gyroscope and line accelerometer signals to implement the filtering function under the Kalman algorithm. The experimental results show that compared with the commonly used filtering methods, this method allows significant reduction of the noise of the gyroscope signal and accurate estimation of the drift of the gyroscope signal, and thus improves the control performance of the system and the stability accuracy.https://www.mdpi.com/1424-8220/19/16/3552MEMS gyroscopeline accelerometernoisedriftKalman filter |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hui Guo Huajie Hong |
spellingShingle |
Hui Guo Huajie Hong Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion Sensors MEMS gyroscope line accelerometer noise drift Kalman filter |
author_facet |
Hui Guo Huajie Hong |
author_sort |
Hui Guo |
title |
Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion |
title_short |
Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion |
title_full |
Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion |
title_fullStr |
Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion |
title_full_unstemmed |
Research on Filtering Algorithm of MEMS Gyroscope Based on Information Fusion |
title_sort |
research on filtering algorithm of mems gyroscope based on information fusion |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2019-08-01 |
description |
As an important inertial sensor, the gyroscope is mainly used to measure angular velocity in inertial space. However, due to the influence of semiconductor thermal noise and electromagnetic interference, the output of the gyroscope has a certain random noise and drift, which affects the accuracy of the detected angular velocity signal, thus interfering with the accuracy of the stability of the whole system. In order to reduce the noise and compensate for the drift of the MEMS (Micro Electromechanical System) gyroscope during usage, this paper proposes a Kalman filtering method based on information fusion, which uses the MEMS gyroscope and line accelerometer signals to implement the filtering function under the Kalman algorithm. The experimental results show that compared with the commonly used filtering methods, this method allows significant reduction of the noise of the gyroscope signal and accurate estimation of the drift of the gyroscope signal, and thus improves the control performance of the system and the stability accuracy. |
topic |
MEMS gyroscope line accelerometer noise drift Kalman filter |
url |
https://www.mdpi.com/1424-8220/19/16/3552 |
work_keys_str_mv |
AT huiguo researchonfilteringalgorithmofmemsgyroscopebasedoninformationfusion AT huajiehong researchonfilteringalgorithmofmemsgyroscopebasedoninformationfusion |
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1724976004738318336 |