<abstract xmlns="http://www.w3.org/1999/xhtml"><p>MEMS gyroscopes can provide useful information for dead-reckoning navigation systems if suitable error compensation algorithm is applied. If there is information from other sources available, usually the Kalman filter is used for this task. This work focuses on improving the performance of the sensor if no other information is available and the integration error should be kept low during periods of still (no movement) operation. A filtering algorithm is proposed to follow bias change during sensor operation to reduce integration error and extend time between successive sensor calibrations. The advantage of the proposed solution is its low computational complexity which allows implementing it directly in the micro-controller of controlling the MEMS gyroscope. An intelligent sensor can be build this way, suitable for use in control systems for mobile platforms. Presented results of a simple experiment show the improvement of the angle estimation. During the 12 hours experiment with a common MEMS sensor and no thermal compensation, the maximum orientation angle error was below 8 degrees.</p></abstract>

MEMS gyroscopes can provide useful information for dead-reckoning navigation systems if suitable error compensation algorithm is applied. If there is information from other sources available, usually the Kalman filter is used for this task. This work focuses on improving the performance of the sensor if no other information is available and the integration error should be kept low during periods of still (no movement) operation. A filtering algorithm is proposed to follow bias change during sensor operation to reduce integration error and extend time between successive sensor calibrations. The advantage of the proposed solution is its low computational complexity which allows implementing it directly in the micro-controller of controlling the MEMS gyroscope. An intelligent sensor can be build this way, suitable for use in control systems for mobile platforms. Presented results of a simple experiment show the improvement of the angle estimation. During the 12 hours experiment with a common MEMS sensor and no thermal compensation, the maximum orientation angle error was below 8 degrees.

Bias Drift Estimation for MEMS Gyroscope Used in Inertial Navigation

Department of Automation, Faculty of Mechanical Engineering

Acta Mechanica et Automatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"Bias Drift Estimation for MEMS Gyroscope Used in Inertial Navigation"}

MEMS gyroscopes can provide useful information for dead-reckoning navigation systems if suitable error compensation algorithm is applied. If there is...

Bias Drift Estimation for MEMS Gyroscope Used in Inertial Navigation

Data publikacji: 15 cze 2017

Zakres stron: 104 - 110

Otrzymano: 08 maj 2016

Przyjęty: 15 maj 2017

DOI: https://doi.org/10.1515/ama-2017-0016

Słowa kluczowe
MEMS Gyroscope, Inertial Navigation, Mobile Platform, Bias Estimation, Angle Of Orientation, Filtering, Gauss Distribution

© 2017 Bialystok University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Bias Drift Estimation for MEMS Gyroscope Used in Inertial Navigation

Data publikacji: 15 cze 2017

Zakres stron: 104 - 110

Otrzymano: 08 maj 2016

Przyjęty: 15 maj 2017

DOI: https://doi.org/10.1515/ama-2017-0016

Słowa kluczoweMEMS Gyroscope, Inertial Navigation, Mobile Platform, Bias Estimation, Angle Of Orientation, Filtering, Gauss Distribution

© 2017 Bialystok University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
MEMS Gyroscope, Inertial Navigation, Mobile Platform, Bias Estimation, Angle Of Orientation, Filtering, Gauss Distribution