Two-Stage Kalman Filter for Estimation of Wind Speed and UAV Flight Parameters Based on GPS/INS and Pitot Tube Measurements

Hajiyev C., Çilden Güler D., Hacizade U.

9th International Conference on Recent Advances in Space Technologies (RAST), İstanbul, Turkey, 11 - 14 June 2019, pp.875-880 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/rast.2019.8767886
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.875-880
  • Keywords: Unmanned Aerial Vehicle, Kalman filter, Wind speed, GPS Pitot Tube, AIRSPEED
  • Istanbul Technical University Affiliated: Yes


Two-stage Kalman filter based estimation algorithm was developed for wind speed and UAV motion parameters. In the first stage, wind speed estimation algorithm is used based on GPS measurements and dynamic pressure measurements. The wind speed is estimated by Kalman filter using GPS and Air Data System (ADS) measurements. For this purpose, Extended Kalman Filter (EKF) was designed, and as state variables, the wind velocity components and ADS pitot scale factor are considered.