Model-Aided Wind Estimation Method for a Tail-Sitter Aircraft

Jingxuan Sun, Boyang Li, Chih Yung Wen, Chih Keng Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)


This paper presents a wind estimation method for a dual-rotor tail-sitter unmanned aerial vehicle with all flight phases. The large flight envelope and the slipstream generated by the propellers introduce extra challenges to estimating the wind field during flight for dual-rotor tail-sitter aircraft. In this method, a synthetic wind measurement is proposed based on a low-fidelity aircraft model and operated as a virtual sensor. This synthetic wind measurement and the data from the pitot tube are fused with an extended Kalman filter. The simulation and experimental results of the developed estimation method show a good estimation of the wind speed and direction in the hovering phase, transition, and cruising phases. The proposed wind estimation method was also tested in the hovering phase using the aerodynamic coefficients of NACA 0012 airfoil and a flat plate instead of the vehicle's model to provide a compromise solution for vehicles with no precise aerodynamic model.

Original languageEnglish
Article number8765354
Pages (from-to)1262-1278
Number of pages17
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number2
Publication statusPublished - Apr 2020


  • Air-data systems
  • tail-sitter
  • unmanned aerial vehicle (UAV)
  • vertical takeoff and landing (VTOL)
  • wind estimation.

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering

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