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The attitude sensor mounted on unmanned systems is required high accuracy attitude under the dynamic acceleration environment for the autonomous attitude control. In order to estimate attitude by using a quaternion based on extended Kalman filter (EKF) , the attitude sensor detects a direction of the gravity by using a tri-axis accelerometer. However, accelerometers are usually sensitive to both the gravity and dynamic accelerations. In this paper, the dynamic accelerations are dealt with explicitly, and two types of algorithms are proposed. In the first approach, measured accelerations are filtered, and divided into the gravity and dynamic accelerations. Using only the gravity, EKF estimates high accuracy of attitude. This algorithm can be realized with relatively small amount of computation, and have a good effect under the short dynamic acceleration environment. The second approach demonstrates adequate performance with EKF which includes the dynamical model of accelerations. This paper shows a critical comparison of attitude estimation algorithms under the dynamic acceleration environment for the autonomous control of unmanned systems.

Development of the Attitude Sensor with Small Scale, Light Weight, Versatility