EKF for Wind Speed Estimation and Sensor Fault Detection Using 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.887-893 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/rast.2019.8767902
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.887-893

Abstract

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. A sensor fault detection algorithm based on EKF innovation process was developed. The results were obtained for noise increment and bias conditions. Estimation errors, normalized innovations and fault detection statistics were obtained.