Research On Motion Prediction Algorithm Of Aircraft Carrier Deck

In the process of fully automatic guidance of carrier-based aircraft landing,deck motion is the main factor affecting the safety of landing.Therefore,compensation of deck motion must be carried out.The key issue in achieving deck motion compensation is to predict deck motion accurately.The problem of deck motion prediction has always been an urgent issue for navies of various countries,and it has also aroused widespread interest among scholars from various countries.Researchers have propsed different methods to solve this problem.One of the most frequently used is the time series analysis method,whitch either the specific state equation of the deck motion or a priori information of the sea waves is needed.Only historical data of the deck motion is required to fit the deck motion.In this paper,Time series analysis method is used to study the deck motion prediction.The specific content is as follows:First,by analyzing the random wave model and its influence on the aircraft carrier deck motion,spectrum analysis of wave energy is performed to obtain the relationship between wave energy,frequency and amplitude,thereby the wave surface equation is determined.The waves are modeled by P-M spectrum,and the cosine waves of different frequencies and phases are superimposed which can obtain the simulation of different levels of waves.On this basis,the aircraft carrier deck motion model under the action of waves is established through empirical methods.The comparison between simulation and actual data verifies the validity and accuracy of the model.Secondly,according to the characteristics of stable autocorrelation of deck motion,auto-regressive model is selected from a variety of time series models to fit the deck motion,and the first-order algorithm based on basic least squares and recursive least squares are designed respectively.Three deck motion estimation algorithms based on basic least squares method and forgetting factor least squares method are designed respectively.Simulation result shows that the prediction error increasing with time can be less than 6% within 5 seconds under three to five sea level,and the error increases with time,which can meet the requirements of fully automatic landing.Thirdly,the maximum likelihood estimate(MLE)method is applied to the deck motion prediction.By analyzing the characteristics of MLE and with the conditional probability density function,the likelihood function of the deck motion model is derived.Based on the maximum likelihood function,the deck motion model is determined.Simulation result which shows that the prediction error increasing with time can be less than 10% within 5 seconds under three to five sea level also meet the requirements of fully automatic landing.However,compared with prediction result of least squares method,the accuracy is slightly insufficient.Finally,based on the prediction of least squares method,improved by empirical mode decomposition and multiple innovation techniques,the deck motion timing signal is decomposed into multiple intrinsic modal functions and signal margins,whitch extends the single-point prediction error to multi-point forecast error to form multiple innovations.Simulation result shows that compared with the previous method,the improved method effectively improves the accuracy of short-term prediction and the effectiveness of long-term prediction.The performance of results above is verified by its application in fully automatic landing simulation.