• DocumentCode
    2199956
  • Title

    Non linear optimum filter based smoothing Interacting Multiple Model for GPS navigation system

  • Author

    Malleswaran, M. ; Vaidehi, V. ; Ramesh, H. ; Bruntha, P. Malin

  • Author_Institution
    Dept. of ECE, Anna Univ. of Technol, Tirunelveli (AUTT), Tirunelveli, India
  • fYear
    2012
  • fDate
    19-21 April 2012
  • Firstpage
    383
  • Lastpage
    388
  • Abstract
    An Interacting Multiple Model Unscented Two Filter Smoother (IMM-UTFS) approach for GPS navigation system is introduced in this paper. The Unscented Kalman Filter (UKF) propagates its state estimate and covariance through unscented transform without any need of linearization. The Interacting Multiple Model (IMM) algorithm obtains its estimate by combining the individual estimate from a number of parallel filters matched to different motion models of the vehicle. This paper adopts the Unscented Two Filter Smoother to the IMM algorithm to increase the navigation estimation accuracy. The dynamic behavior of the vehicle is analyzed and the simulation results show that IMM-UTFS can improve overall navigation accuracy as compared to traditional filters like UKF and multiple model filters like IMM-UKF.
  • Keywords
    Global Positioning System; Kalman filters; nonlinear filters; vehicle dynamics; GPS navigation system; Global Positioning System; IMM-UTFS approach; navigation estimation accuracy; nonlinear optimum filter; parallel filter; smoothing interacting multiple model; unscented Kalman filter; unscented two filter smoother approach; vehicle dynamic behavior; Estimation; Filtering algorithms; Navigation; Noise; Smoothing methods; Vehicle dynamics; Vehicles; GPS; Interacting Multiple Model (IMM); Interacting Multiple Model Unscented Two Filter Smoother (IMM-UTFS); Unscented Kalman Filter (UKF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Recent Trends In Information Technology (ICRTIT), 2012 International Conference on
  • Conference_Location
    Chennai, Tamil Nadu
  • Print_ISBN
    978-1-4673-1599-9
  • Type

    conf

  • DOI
    10.1109/ICRTIT.2012.6206794
  • Filename
    6206794