In order to improve the passive tracking situation of receiver aircraft for drogue during the docking phase of AAR (autonomous aerial refueling), a strategy of AAR predictive guidance scheme based on NAR (Nonlinear Auto Regressive) neural network model is proposed. The NAR neural network model is used to predict the future position of the drogue as the target point of receiver aircraft. The simulation is carried out by Monte Carlo target test. The simulation results indicate that the proposed algorithm possesses high prediction precision and significantly enhances the success rate of AAR, which is of crucial importance in achievement of AAR technique.
Predictive Guidance Scheme with NAR Neural Network for Autonomous Aerial Refueling
01.08.2018
449744 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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