• DocumentCode
    149539
  • Title

    Gaussian-sum cubature Kalman smoothers for bearings-only tracking

  • Author

    Pei Hua Leong ; Arulampalam, Sanjeev ; Lamahewa, Tharaka A. ; Abhayapala, Thushara D.

  • Author_Institution
    Res. Sch. of Eng., Australian Nat. Univ. (ANU), Canberra, ACT, Australia
  • fYear
    2014
  • fDate
    21-24 April 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    In this paper, a fixed-lag and a fixed-interval Gaussian-sum cubature Kalman smoother are proposed for the bearings-only tracking problem. The smoothers are of the forward-backward type and they utilise the Gaussian-sum cubature Kalman filter with improved robustness presented by the authors in [1]. Simulation results show that both the fixed-lag and fixed-interval smoothers exhibit improved accuracy over their filtering counterpart and outperform other existing smoothers of the same type for this problem, with the root-mean-square error overlapping the Cramér-Rao lower bound.
  • Keywords
    Gaussian processes; Kalman filters; direction-of-arrival estimation; least mean squares methods; smoothing methods; target tracking; Cramer-Rao lower bound; Gaussian-sum Cubature Kalman smoother; bearings-only tracking problem; fixed interval smoother; fixed lag smoother; root mean square error overlapping; Accuracy; Bayes methods; Covariance matrices; Kalman filters; Noise measurement; Smoothing methods; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP), 2014 IEEE Ninth International Conference on
  • Conference_Location
    Singapore
  • Print_ISBN
    978-1-4799-2842-2
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2014.6827589
  • Filename
    6827589