Measurement Optimization of Rolling Angle and Pitch Angle Based on Fuzzy Compensation and Kalman Filter

To reduce errors between measurement angles and actual rotation angles when a gyroscope and an accelerometer are rotating around their own X-axis or Y-axis, a method based on fuzzy compensation and Kalman filter is proposed in this paper. Compensation dosages of fuzzy compensation algorithm are related to error characteristics between measurement angles and actual rotation angles which can be detected through experiments, thus gyroscope and accelerometer rotation angles compensated with compensation dosages can be obtained. Finally, Kalman filter algorithm is proposed to fuse these two angles to one angle which will be regarded as final rotation angle. The experimental results show that rotation errors optimized by fuzzy compensation and Kalman filter algorithm are reduced significantly when the gyroscope and accelerometer are rotating around their own X-axis or Y-axis.