Development of a New Airport Unusual-Weather Detection System with Aircraft Surveillance Information

Shau-Shiun Jan, Ya Tzu Chen

Research output: Contribution to journalArticle

Abstract

This paper proposes a new aviation unusual-weather detection system constructed to augment existing aviation unusual-weather alert systems. Due to a lack of ground meteorological stations with sufficient ground altitude near airports, existing aviation unusual-weather alert systems can only detect unusual-weather conditions near the ground surface. Thus, this paper uses the automatic dependent surveillance - broadcast (ADS-B) signal transmitted by commercial aircraft to acquire vertical weather information for low-level weather conditions. Specifically, we propose an aviation unusual-weather detection model to establish the system using both the aircraft irregular-movement detection algorithm and the machine learning method. The performance of the proposed unusual-weather detection model is validated with actual ADS-B signals from several flights collected at the airport. The experiment results show the accuracy rates of aviation normal/unusual-weather classification above 96% and false positive rates below 1% for decent flight phases.

Original languageEnglish
Article number8754800
Pages (from-to)9543-9551
Number of pages9
JournalIEEE Sensors Journal
Volume19
Issue number20
DOIs
Publication statusPublished - 2019 Oct 15

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airports
surveillance
Airports
weather
Aviation
aircraft
Aircraft
aeronautics
Learning systems
flight
commercial aircraft
weather stations
machine learning
ground stations
Experiments

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

Cite this

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abstract = "This paper proposes a new aviation unusual-weather detection system constructed to augment existing aviation unusual-weather alert systems. Due to a lack of ground meteorological stations with sufficient ground altitude near airports, existing aviation unusual-weather alert systems can only detect unusual-weather conditions near the ground surface. Thus, this paper uses the automatic dependent surveillance - broadcast (ADS-B) signal transmitted by commercial aircraft to acquire vertical weather information for low-level weather conditions. Specifically, we propose an aviation unusual-weather detection model to establish the system using both the aircraft irregular-movement detection algorithm and the machine learning method. The performance of the proposed unusual-weather detection model is validated with actual ADS-B signals from several flights collected at the airport. The experiment results show the accuracy rates of aviation normal/unusual-weather classification above 96{\%} and false positive rates below 1{\%} for decent flight phases.",
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Development of a New Airport Unusual-Weather Detection System with Aircraft Surveillance Information. / Jan, Shau-Shiun; Chen, Ya Tzu.

In: IEEE Sensors Journal, Vol. 19, No. 20, 8754800, 15.10.2019, p. 9543-9551.

Research output: Contribution to journalArticle

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