A Novel MEMS Gyroscope In-Self Calibration Approach

Abstract

This paper presents a novel approach for hand-held low-cost MEMS (micro-electro-mechanical system) gyroscope in-self calibration. This method does not need the support of external high-precision equipment compared with traditional calibration scheme and can be accomplished by user hand rotation. In this approach, Kalman filter is designed to perform the calibration procedure and estimate gyroscope bias error, scale factor error and non-orthogonal error. The system observability is analyzed and the dynamic rotating conditions under which the sensor errors become observable are derived. The design principles of optimal calibration procedure are provided as well. Both simulated and practical experiments are carried out to test the validation of the proposed calibration algorithm. The achieved results demonstrate that the introduced approach can provide promising calibration scheme for the low-cost MEMS gyroscope.

Investigation of FBG Linear/Angular Acceleration Sensor for Novel Type Inertial Measurement

“…Apart from the aforementioned measurement noise caused by EMI, MEMS-based IMU sensors are known to exhibit large errors owing to the use of relatively inaccurate gyroscope sensors [15]. A gyroscope sensor simply measures the physical quantity of angular speed without a reference value, potentially introducing greater errors in roll, pitch angle measurements than an acceleration sensor, which measures gravitational acceleration as its reference value to determine the change in the roll and pitch angles (orientation) of an object [16]. For this reason, some researchers expect that IMU sensors without gyroscopes will be increasingly used in future industries [17].…”