Prediction of vertical motions for landing operations of UAVs

This paper outlines a novel and feasible procedure to predict vertical motions for safe landing of unmanned aerial vehicles (UAVs) during maritime operations. In the presence of stochastic sea state disturbances, dynamic relationship between an observer and a moving deck is captured by the proposed identification model, in which system order is specified by a new order-determination principle based on Bayes Information Criterion (BIC). In addition, the resulting system model is extended to develop accurate multi-step predictors for estimation of vertical motion dynamics. Simulation results demonstrate that the proposed prediction approach substantially reduces the model complexity and exhibits excellent prediction performance, making it suitable for integration into ship-helicopter approaches and landing guidance systems.