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A General Framework for Flight Maneuvers Automatic Recognition

Author

Listed:
  • Jing Lu

    (College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
    College of Computer Science, Civil Aviation Flight University of China, Guanghan 618307, China)

  • Hongjun Chai

    (College of Computer Science, Civil Aviation Flight University of China, Guanghan 618307, China)

  • Ruchun Jia

    (Wangjiang Campus, Sichuan University, Chengdu 610065, China)

Abstract

Flight Maneuver Recognition (FMR) refers to the automatic recognition of a series of aircraft flight patterns and is a key technology in many fields. The chaotic nature of its input data and the professional complexity of the identification process make it difficult and expensive to identify, and none of the existing models have general generalization capabilities. A general framework is proposed in this paper, which can be used for all kinds of flight tasks, independent of the aircraft type. We first preprocessed the raw data with unsupervised clustering method, segmented it into maneuver sequences, then reconstructed the sequences in phase space, calculated their approximate entropy, quantitatively characterized the sequence complexity, and distinguished the flight maneuvers. Experiments on a real flight training dataset have shown that the framework can quickly and correctly identify various flight maneuvers for multiple aircraft types with minimal human intervention.

Suggested Citation

  • Jing Lu & Hongjun Chai & Ruchun Jia, 2022. "A General Framework for Flight Maneuvers Automatic Recognition," Mathematics, MDPI, vol. 10(7), pages 1-15, April.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:7:p:1196-:d:787910
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