Angular velocity estimation of rotating plate using extended Kalman filter with accelerometer bias model

There has been researches on the gyro-free inertial navigation system (GF-INS), in which angular velocities are obtained from array of accelerometers instead of gyroscopes. The GF-INS can be effectively used for vehicles with high rotation rate when gyroscopes cannot provide the angular velocities due to their operating limitations. In order to obtain angular velocity, the measured accelerometer outputs are integrated and/or static model based estimators are used. When the integration is used, estimation performance of the angular velocity may be severely degraded due to the accelerometer error and depends on the initial velocity error. There is sign ambiguity problem of the angular velocity when the static model based estimator is used. In this paper, an angular velocity estimation algorithm of a rotating plate from centripetal acceleration and tangential acceleration measurements is proposed using an extended Kalman filter (EKF) with a random bias error model of the accelerometer. By using the EKF, effect of accelerometer error and initial velocity error can be reduced and sign ambiguity problem can be resolved. In order to show the validity of the proposed algorithm, an experimental setup is constructed. The angular velocity is estimated from outputs of a Micro-Electro Mechanical System accelerometer triad placed on the rotating plate. It can be seen from the results that performance of estimates by the EKF is better than those of other methods.