A Novel Method to Improve the Accuracy of Low-cost Gyroscope-based Attitude Estimation by Fusing Angular Acceleration Sensors

Gyroscope-based attitude estimation system has the problem of attitude drift under long-term operation conditions, which is particularly obvious on low-cost gyroscopes. As a new type of inertial sensor, the angular acceleration sensor can directly sense the angular acceleration of the carrier. The error characteristics and the mechanism by which an angular acceleration sensor is sensitive to changes in attitude are different from those of a gyroscope. Therefore, it is a feasible solution to use angular acceleration data to provide error correction for the gyroscope, thereby improving the accuracy of attitude estimation. In this paper, a novel method is proposed to improve the attitude estimation accuracy of low-cost gyroscope by fusing angular acceleration sensors. Based on the data characteristics of two inertial sensors, two different state variables and corresponding observation variables are designed, and the information fusion of the two sensors is realized through Kalman filtering. A synchronous data acquisition device was designed to conduct experimental verification. The experimental results show that the proposed method can improve the attitude estimation accuracy of low-cost gyroscopes under long-term operation conditions.