Quaternion-based orientation estimation with static error reduction

Tracking the orientation or attitude of an object has many applications in various research fields. This paper presents a tracking system which estimates the orientation of an object using an angular rate sensor, accelerometer, and magnetometer. For the combined usage of the sensors, the Kalman filter and the Factored Quaternion Algorithm (FQA) are applied to the proposed system. We also propose a method to eliminate the drift effect of the angular rate sensor in static state. The experimental results show that the proposed tracking system can estimate an accurate rotation of an object and can eliminate the drift effect in static state.