• DocumentCode
    115376
  • Title

    Tracking of the UAV trajectory on the basis of bearing-only observations

  • Author

    Miller, Alexander ; Miller, Boris

  • Author_Institution
    Inf. Transm. Problems, Moscow, Russia
  • fYear
    2014
  • fDate
    15-17 Dec. 2014
  • Firstpage
    4178
  • Lastpage
    4184
  • Abstract
    This work considers the tracking of the UAV (unmanned aviation vehicle) path on the basis of bearing-only observations including azimuth and elevation angles. The significance of this research becomes clear in the case when GPS either does not work at all or produce the high level of the measurement errors. It is assumed that either UAV´s opto-electronic cameras or radar systems are able to capture the angular position of objects with known coordinates and to measure the azimuth and elevation angles of the sight line. Such measurements involve the real position of UAV in implicit form, and therefore some of nonlinear filters such as Extended Kalman filter (EKF) or others may be used in order to implement these measurements for UAV control. However, all such approximate nonlinear filters produce the estimations with unknown bias and quadratic errors. This peculiarity prevents the data fusion in more or less regular way. Meanwhile, there is well-known method of pseudomeasurements which reduces the estimation problem to the linear settings. In this article we develop the modified pseudomeasurement method without bias and with the possibility to evaluate the second moments of the UAV position errors which helps to realize the data fusion. On the basis of this filtering algorithm we develop the control algorithm for tracking of given reference path under external perturbation and noised angular measurements. Modelling examples show the nice performance of the control algorithm.
  • Keywords
    autonomous aerial vehicles; nonlinear filters; trajectory control; EKF; GPS; UAV control; UAV position errors; UAV tracking; approximate nonlinear filters; azimuth angle; bearing-only observations; control algorithm; data fusion; elevation angle; extended Kalman filter; external perturbation; measurement errors; modified pseudomeasurement method; noised angular measurements; object angular position; opto-electronic cameras; quadratic errors; radar systems; unmanned aviation vehicle; Coordinate measuring machines; Equations; Estimation; Mathematical model; Position measurement; Standards; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2014 IEEE 53rd Annual Conference on
  • Conference_Location
    Los Angeles, CA
  • Print_ISBN
    978-1-4799-7746-8
  • Type

    conf

  • DOI
    10.1109/CDC.2014.7040040
  • Filename
    7040040