Automatic sea state estimation with online trust measure based on ship response measurements

The ever-changing sea state constitutes an integral part of situational awareness for vessels at sea. In this paper, a computationally efficient sea state estimation algorithm is extended by (1) automatic gain and tolerance calculation, and (2) trust measure for wave filtering condition identification. The resulting algorithm can run online in a control system without the need of user input, producing estimates of sea state parameters (significant wave height, peak wave frequency and main propagation direction), while simultaneously monitoring the quality of the estimates produced by identifying when wave filtering occurs. The algorithm is developed for application in dynamic positioning (DP) control systems, where the vessel has zero (or low) forward speed. The estimation method is tested with realistic values of measurement noise and sampling in terms of comprehensive time series simulations based on both long-and short-crested wave conditions. The sea state estimates correspond well with a state-of-the-art Bayesian estimation approach. This indicates that the simplifications made in order to enhance the computational speed, has not affected the quality of the estimates to any significant extent. The trust measure correctly identifies when wave filtering occurs in all simulated scenarios.