Dual rate Kalman filter considering delayed measurement and its application in visual servo

This paper describes a Kalman filter for a class of linear system in which: 1) The sampling time of measurement is longer than the control period. 2) The measurement is delayed. Using the delayed measurement and the present and past time predicted state, the pseudo-measurement in present time is constructed. The optimal Kalman gain is designed to minimize the trace of the covariance of estimation error. A dual rate recursive algorithm is proposed to estimate the state synchronously with the control signal. A visual servo system is demonstrated to verify the effectiveness of the proposed method.