Model identification of ship turning maneuver and extreme short-term trajectory prediction under the influence of sea currents

Abstract

To improve the accuracy of extreme short-term prediction of ship motion under environmental disturbances, a method to identify the motion model of ship turning maneuver and predict the ship extreme short-term trajectory with the influence of ocean currents is studied. Under the influence of ocean currents, a ship motion response model is identified based on the least squares method, and a ship extreme short-term trajectory prediction model is established. The velocity distribution extraction algorithm, center point restoration algorithm, and weighted derivation algorithm are proposed to extract the current direction and the velocity of the turning test. By integrating the current information and ship response characteristics in the extreme short-term ship prediction model, the extreme short-term segmented prediction of the ship trajectory is realized, and the current information is corrected online according to the prediction errors. The real test results show that, compared with the prediction method based on the ship dynamic model, inertia derivation and current compensation, the proposed extreme short-term trajectory prediction method has higher accuracy. Specifically, the prediction error of the proposed method is reduced by 80.6%, 89.3%, and 54.7% than abovementioned methods, respectively.