Aircraft atypical approach detection using functional principal component analysis

被引：23

作者：

Jarry, Gabriel ^{[1
]}

Delahaye, Daniel ^{[1
]}

Nicol, Florence ^{[1
]}

Feron, Eric ^{[2
]}

机构：

[1] Univ Toulouse, Ecole Natl Aviat Civile, 7 Ave Edouard Belin, F-31400 Toulouse, France

[2] King Abdullah Univ Sci & Technol, Div Elect Comp & Math Sci & Engn, Thuwal 23955, Saudi Arabia

来源：

JOURNAL OF AIR TRANSPORT MANAGEMENT | 2020年 / 84卷

关键词：

Approach path management; Atypical flight event; Non-compliant approach; Functional principal component analysis; Unsupervised learning; Anomaly detection;

D O I：

10.1016/j.jairtraman.2020.101787

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

In this paper, a post-operational detection method based on functional principal component analysis and clustering is presented and compared with regard to designed operational criteria. The methodology computes an atypical scoring on a sliding window. It enables not only to detect but also to localize where trajectories deviate statistically from the others. The algorithm is applied to the total energy management, estimated from ground-based data, during approach and landing. The detected atypical flights show non-nominal energy behaviors such as glide interceptions from above or high speed approaches. This promising methodology could help to enhance flight data analysis and safety, highlighting non-monitored behaviors.

引用

页数：10