Wavelet Clustering Of Aircraft Trajectory In Terminal Airspace And Its Application

As air traffic flow in terminal airspace grows increasingly, the efficiency of air route network is decreasing. By clustering of aircraft trajectory in terminal airspace, it can regulate the structure of air route network and sectors, which will improve the operational efficiency of air traffic flow. In the area of aircraft trajectory clustering nowadays, there's a low level of automation and many difficulties to identify trajectory outliers. These issues affect the scientific and automation level of traffic identification, and there need an thorough study for flight trajectory clustering.To solve these problems, wavelet clustering method of aircraft trajectory in terminal airspace was put forward, which has high degree of clustering automation and easy recognition of trajectory outliers.Trajectories similarity matrix was established based on 3D spatial grids, and a trajectories similar characteristic subspace was induced, a 2D similar feature pattern was obtained. After a digitization, wavelet transform and clustering, prevailing traffic flows and outliers were identified at the same time.Finally, the experimental results show that the problem of original high-dimensional trajectory data couldn't be used in wavelet clustering untreated was addressed, and Xian terminal airspace's 352 trajectories was partitioned into 4 clusters automatically and 21 outliers were recognized obviously without artificial guide.The results accord with the reality in Xian terminal airspace, which shows the feasibility and effectiveness of the algorithm. Then, combing experiment results with the reality, some suggestions for the improvement of Xian terminal airspace's structure was supplied.Without manual interposing, this method can partition clustering and detect trajectory outlier effectively. By combining practical, it can provide substantial reference for air route network and the configurations of sectors in terminal airspace.