Aircraft Trajectory Prediction And Aviation Safety In Ads-b Failure Conditions Based On Neural Network

This paper presents a review of the literature related to aircraft trajectory prediction. Various methods have been developed to improve the accuracy of trajectory prediction, such as state estimation model, dynamic model and machine learning model. Kang et al. used visual sensors to obtain the position and attitude of the aircraft, and then deduced the conventional specific extreme power and an energy maintaining specific power. Yepes et al. uses a hybrid estimation algorithm to estimate the status and flight mode of an aircraft, and then uses air traffic regulations, aircraft flight plans, and environmental knowledge to infer the pilot’s intentions. Liu et al. proposed an intent based trajectory prediction (IBTP) algorithm. Liu et al. also presents a stochastic linear hybrid system to describe the dynamics of an aircraft with varying flight conditions.