摘要
Dear Editor,This letter addresses the challenge of forecasting the motion of real-world vessels over an extended period with a limited amount of available data.By employing stochastic differential equation(SDE)modeling,we integrate both deterministic and stochastic components of the available information.Subsequently,we establish a recursive prediction methodology based on Bayes’rule to update the model state when new measurements are received.Furthermore,we develop a stochastic model tailored specifically to vessel dynamics and introduce an approximation method to tackle computational complexities.Finally,we present an application example and conduct a comparative experiment to validate the effectiveness and superiority of the proposed method.
基金
supported by the National Natural Science Foundation of China(62073019)
the Key R&D Program of Hebei Province(22340301D)
China Postdoctoral Science Foundation(2021M703021)
Hebei Postdoctoral Science Foundation(B2021003031)。