A Sine-Summation Algorithm for the Prediction of Ship Deck Motion

Abstract

Landing a fixed-wing aircraft on a moving aircraft carrier is a risky and inefficient process. Having an accurate prediction of ship deck motion decreases the risk posed to both the pilot and the aircraft and increases the efficiency of landing maneuvers. The present work proposes the use of a sine-summation algorithm to predict future ship motion. The algorithm decomposes recorded ship acceleration data into its characteristic harmonic parameters using a fast Fourier transform. The harmonic parameters are then used in a summation of sine waves to create a fit for the acceleration data, which is projected into future time intervals to predict ship motion. An aircraft carrier can supply the prediction made by the algorithm to an autopilot, which then decides to land or make another attempt. Included in this work is a brief overview of ship motion with six degrees of freedom and a description of the method. The results generated by the algorithm are presented for a specific ship motion dataset to provide a point of comparison between the proposed method and other common methods used. The proposed method appears to be accurate in comparison to similar prediction methods, while reducing the computational cost required to make a prediction.

Disturbance rejection based on discrete-time adaptive preview control for unmanned aerial vehicle shipboard landing under structure damage

“…where P d = [ X d , Y d , H d ] T , X s , Y s , H s denote the translation motion components, θ s , ψ s , ϕ s denote the angular motion components, and they can be expressed by a summation of sine waves with various amplitudes and frequencies. 18 Moreover, the deck motion can be predicted in advance with prediction algorithms, such as AR, 19 Kalman filters, 20 and deep learning. 21…”