Real-time estimation of a ship's attitude

During subsea lifting operations in harsh sea conditions, the involved crane system is subjected to extensive dynamic forces due to vertical vessel motion. Thus, active heave compensation systems can be used to compensate for vertical vessel motion and to reduce forces acting on the crane structure. Furthermore, such systems allow an exact positioning of the load on the seabed. However, active heave compensation systems always require knowledge about the vertical position of the crane depending on the ship's heave, roll, and pitch motion. Hence, an attitude estimation method for ships during subsea lifting operations is proposed. To estimate the roll and pitch motion of a vessel with high accuracy, rotation rate sensors are fused with accelerometers using an Extended Kalman Filter. Since an exact knowledge of the yaw motion is not required to determine the crane's vertical motion, the yaw angle is stabilized around zero with an additional virtual sensor signal. The attitude estimation algorithm is evaluated with simulation and measurement results from an experimental setup.