MEMS Gyroscope Null Drift and Compensation Based on Neural Network
This study investigates the effects of temperature on micro-electro mechanical system (MEMS) gyroscope null drift and methods and efficiency of temperature compensation. First, this study uses in-house-designed inertial measurement units (IMUs) to perform temperature effect testing. The inertial measurement unit is placed into the temperature control chamber. Then, the temperature is gradually increased from 25 °C to 80 °C at approximately 0.8 degrees per minute. After that, the temperature is decreased to -40 °C and then returning to 25 °C. During these temperature variations, the temperature and static gyroscope output observes the gyroscope null drift phenomenon. The results clearly demonstrate the effects of temperature on gyroscope null voltage. A temperature calibration mechanism is established by using a neural network model. With the temperature calibration, the attitude computation problem due to gyro drifts can be improved significantly.
J. K. Shiau et al., "MEMS Gyroscope Null Drift and Compensation Based on Neural Network", Advanced Materials Research, Vols. 255-260, pp. 2077-2081, 2011