Optimization of Flight Procedure Method Based on Track Clustering

Flight procedure devising is an important part to ensure flight safety, and the benchmark of aircraft safe operation. Therefore, if flight procedures are not suitable for the operating environment will also produce serious potential safety hazards. Based on the track information of the actual operation of an airport, combined with BP neural network and K-means algorithm, a new track clustering model is constructed. Through the cluster analysis of the departure track of the airport, the clustering center of the track is obtained. Combined with the inherent flight procedure of the airport, it is found that there are great differences between the actual operation track and the inherent flight procedure. After investigating and analyzing the causes of the differences, the program improvement scheme is put forward. Finally, the track clustering results are compared with the flight program optimization results, and the simulation analysis is carried out by using air top software. The results show that the new program can better adapt to the actual operation of the aircraft.