Unidirectional and multi-directional wave estimation from ship motions using an Adaptive Kalman Filter with the inclusion of varying forward speed

This paper aims at estimating both unidirectional and multi-directional waves from noisy measured ship motion data, with a focus on the inclusion of the vessel’s forward speed to reflect real-world operating conditions. The technique is based on an Adaptive Kalman Filter for estimating wave elevation and wave spectrum parameters, including significant wave height, peak period, and wave direction. The proposed method was tested using simulated ship motion data, and its performance was evaluated by comparing the estimated wave spectrum with reference values used in the simulation model and with results from a widely used baseline frequency domain approach. The results demonstrate that the method effectively estimates the wave spectrum in a short measuring window with a reasonable degree of accuracy when accounting for varying forward speed, indicating strong potential for real-time wave estimation to aid in improving navigation, safety, and operational efficiency. • An Adaptive Kalman Filter is applied for wave spectrum estimation based on vessel motions. • The estimation includes vessel forward speed and unknown measurement noise. • Favorable comparison is made between estimated and simulated sea states.