Application Of Strongly Tracking Kalman Filter In MEMS Gyroscope Bias Compensation
In this paper,we make a research about a integrated system.The system consists of two main parts: micro-electro-mechanical systems(MEMS)gyroscopes and compass.In order to eliminate the temperature drift bias of MEMS gyroscope,we use a strong tracking Kalman filter and chooses an adaptive algorithm.We established a model about the bias of the temperature of the gyroscope.The parameters of the model are selected for the state variables to change intelligently with the temperature to increase the precision of the MEMS gyroscope1-2.In the static temperature experiment,the compensated heading error is less than 0.7°.We can draw a conclusion that the traditional Kalman filter compensation method,multiple linear regression compensation method,improved least squares method and strong tracking Kalman adaptive filtering algorithm all can compensate the gyroscope drift bias,but the adaptive filtering algorithm can be more accurate about the compensation of MEMS gyro drift bias,and eliminate the impact of temperature on its accuracy.
MEMS gyroscope gyro bias strong tracking adaptive Kalman filter error compensation
Liu Hong Dan Shu Xiong Ying Li Xi Sheng
School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing 100083,China
国际会议
郑州
英文
1-7
2017-04-29（万方平台首次上网日期，不代表论文的发表时间）