Resumen
With the development of emerging techniques, maritime autonomous surface ships (MASS) have attracted much attention, and the remote control ships? future seems promising. However, due to communication issues, ship?shore transmission faces the challenge of time delay. The use of the transmitted information without compensation could reduce the effectiveness of controlling or could cause the remote control to be unstable. To eliminate the negative effects of uncertain delays during navigation, an Augmented State Cubature Kalman Filter (AS-CKF) is proposed. First, the uncertainty of the transmission delays is modeled using a probability density function (PDF). Second, the ship?s states are updated and estimated using the delayed observed data, and then the real state of the ship is simultaneously corrected in the augmented state vector. In this way, the delay compensation problem becomes a one-step prediction problem. To test the proposed AS-CKF for MASS, we simulate scenarios with the remote control ship under different communication time delays. The results show improvements compared to the traditional CKF, EKF, or AS-EKF, which indicates the potential of the proposed methods in remote control MASS.