Journal of Applied Optics, Volume. 45, Issue 2, 453(2024)

Aircraft type identification method based on FBG sensing array of smart runway

Sheng LI1,*... An LIU2 and Jinding GUO2 |Show fewer author(s)
Author Affiliations
  • 1National Engineering Research Center of Fiber Optic Sensing Technology and Networks, Wuhan University of Technology, Wuhan 430070, China
  • 2School of Information Engineering, Wuhan University of Technology, Wuhan 430070, China
  • show less

    Aiming at the shortcomings that the current aircraft type identification method is easily affected to environmental influences, a novel aircraft type identification method based on fiber optic Bragg grating (FBG) sensing array of smart runway was proposed. The distributed vibration response of the aircraft taxiing was collected by using the FBG array buried horizontally under the pavement. By analyzing the time-history impulse response features of multiple measurement areas, the time differences between the main and auxiliary landing gears passing through the optical cable were determined. The taxiing trajectory of the aircraft was sensed by the FBG array buried longitudinally under the pavement, through which the taxiing speed of the aircraft was determined by polynomial fitting. The aircraft type was identified based on matching relationship between the test value and the theoretical value of the main and auxiliary landing gears of the aircraft. The aircraft information in the test flight and the initial two-month operation of a certain airport were used for method verification. The results show that the identification accuracy of the proposed identification method can reach 98.44%, which can effectively distinguish the B757, B738, A320 and A321 models.

    Keywords
    Tools

    Get Citation

    Copy Citation Text

    Sheng LI, An LIU, Jinding GUO. Aircraft type identification method based on FBG sensing array of smart runway[J]. Journal of Applied Optics, 2024, 45(2): 453

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Research Articles

    Received: Apr. 19, 2023

    Accepted: --

    Published Online: May. 28, 2024

    The Author Email: LI Sheng (lisheng@whut.edu.cn)

    DOI:10.5768/JAO202445.0208002

    Topics