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The safety of air transportation depends on the level of airplane deviations from preplanned trajectory and cleared flight level. Minimums of vertical separation are used as perils for safe airplane deviation from required altitude of flight level. Vertical separation minimums are designed to take into account errors in pressure altitude measurements. In the paper, we consider airplane flight situation classification based on airplane deviation from cleared flight level. We analyze a full group of classes which include normal flight, high deviation, complicated, emergency, and catastrophic situations. A maximum posterior probability method is used for classification. A Gaussian function is used as a conditional probability density function of each class. A prior probability of each class is estimated by statistical data analysis of historical flight realizations. Proposed classifier could be used in the Flight Management System for safety monitoring and alerting or could be integrated into algorithms of surveillance data processing in automatic air traffic control systems.

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Classification of Flight Situation Based on Risk of Flight Level Loss for Improved Airspace Safety

  • 会议论文

  • 发表日期：

    2025年

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  • Ivan Ostroumov,
  • Yurii Bezkorovainyi,
  • Oleksii Holubnychyi,
  • Olha Sushchenko,
  • Oleksandr Solomentsev,
  • Maksym Zaliskyi,
  • Yuliya Averyanova,
  • Kostiantyn Cherednichenko,
  • Olena Sokolova,
  • Viktoriia Ivannikova,
  • Borys Kuznetsov,
  • Ihor Bovdui,
  • Tatyana Nikitina,
  • Roman Voliansky

摘要

The safety of air transportation depends on the level of airplane deviations from preplanned trajectory and cleared flight level. Minimums of vertical separation are used as perils for safe airplane deviation from required altitude of flight level. Vertical separation minimums are designed to take into account errors in pressure altitude measurements. In the paper, we consider airplane flight situation classification based on airplane deviation from cleared flight level. We analyze a full group of classes which include normal flight, high deviation, complicated, emergency, and catastrophic situations. A maximum posterior probability method is used for classification. A Gaussian function is used as a conditional probability density function of each class. A prior probability of each class is estimated by statistical data analysis of historical flight realizations. Proposed classifier could be used in the Flight Management System for safety monitoring and alerting or could be integrated into algorithms of surveillance data processing in automatic air traffic control systems.