• DocumentCode
    3075070
  • Title

    Attitude estimation of a simulated flight and GPS positioning with Kalman filter

  • Author

    Querino Filho, Luiz C. ; Rodrigues Filho, Julio F. ; da Silva, Natassya B. F. ; Castelo Branco, Kalinka

  • Author_Institution
    Univ. of Sao Paulo, Sao Carlos, Brazil
  • fYear
    2015
  • fDate
    9-12 June 2015
  • Firstpage
    742
  • Lastpage
    750
  • Abstract
    The Kalman filter is an algorithm used for data estimation and sensor fusion. It has been used for decades in several projects, especially in the aerospace industry, being the Apollo program for lunar explorations one of the first to apply the filter. As a way to analyze the practical Kalman filter application in real situations, this paper shows its use in the estimation of the horizontal attitude for an aircraft flight. The experiments were produced inside the X-Plane simulator, through its plugin system and with the estimation of data gathered from the simulated gyroscope. Additionally, a mobile application was developed to show the Kalman filter output for GPS positioning estimation under uncertainty conditions - in this case, inside a building. Results show the data obtained by the filter and a comparison of the values before and after its application.
  • Keywords
    Kalman filters; aerospace industry; aerospace simulation; aircraft; attitude measurement; gyroscopes; mobile computing; sensor fusion; Apollo program; GPS positioning estimation; Kalman filter; X-Plane simulator; aerospace industry; aircraft flight; data estimation; gyroscope; horizontal attitude estimation; lunar explorations; mobile application; plugin system; sensor fusion; simulated flight; Aerodynamics; Aerospace control; Aircraft; Aircraft propulsion; Estimation; Kalman filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Unmanned Aircraft Systems (ICUAS), 2015 International Conference on
  • Conference_Location
    Denver, CO
  • Print_ISBN
    978-1-4799-6009-5
  • Type

    conf

  • DOI
    10.1109/ICUAS.2015.7152357
  • Filename
    7152357