Flight behavior recognizing in terminal area based on support vector machine

Author

Hu, Laihong ; Sun, Fuchun ; Liu, Huaping ; Xu, Hualong

Author_Institution

Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China

fYear

2010

fDate

7-9 July 2010

Firstpage

90

Lastpage

95

Abstract

The increasing demand for air travel is stressing the current Air Traffic Control (ATC). This is likely to cause both safety and performance degradation in the near future. In order to solve this problem, increasing the automation level of ATC is an important development direction. So flight behavior recognizing is becoming a key technique for ATC, for it is the basis of other function of ATC, such as landing scheduling, conflict detection, and so on. This paper introduced support vector machine (SVM) to solve flight behavior recognizing in terminal area, and designed multi-classification algorithm flow. The simulation results show that SVM is equal to this task.

Keywords

aerospace computing; air traffic control; behavioural sciences computing; support vector machines; air traffic control; flight behavior; multiclassification algorithm flow; support vector machine; Accuracy; Air traffic control; Aircraft; Airports; Classification algorithms; Support vector machines; flight behavior; recognizing; support vector machine;

fLanguage

English

Publisher

ieee

Conference_Titel

Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-8041-8

Type

conf

DOI

10.1109/COGINF.2010.5599761

Filename

5599761