The rapid and accurate aircraft trajectory prediction is the basis and guarantee for the realization of the above methods. The purpose of these methods is to improve air traffic efficiency and ensure air traffic safety. In recent years, automatic and intelligent methods of air traffic control, such as aircraft conflict detection and resolution, sequence of approach and departure, and trajectory-based operation, have become increasingly popular. Flight delays not only bring direct economic losses to passengers and airlines but also affect the development of the national economy. With the development of civil aviation industry, there are more and more aircraft on the flight path, the flight spacing is smaller and smaller, and the air traffic safety situation is more and more serious. It is proved that the optimized method based on historical track data is effective and reliable, and the accuracy of 4D track prediction is improved greatly. By comparing the flight forecast time with the real crossing time, it is found that the average error of the improved 4D forecast crossing time is less than 5% of the flight time, which is obviously better than that before optimization. On the basis of the traditional aircraft performance model, this paper puts forward the aircraft maneuver mode using strategy and introduces the high-altitude wind information from the weather information into the aircraft 4D model to optimize the aircraft 4D trajectory calculation model. This project collected a large amount of historical data to form a control experience database and mined the historical database to obtain control experience and flight intention.
Meanwhile, method based on historical data mining cannot accurately couple with real-time conditions such as weather and also cause computational efficiency problems.
Traditional 4D trajectory prediction based on aircraft performance models and flight procedures does not consider control handover rules.
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