• DocumentCode
    2620799
  • Title

    Stochastic approximation for optimal observer trajectory planning

  • Author

    Singh, Sumeetpal ; Vo, Ba-Ngu ; Doucet, Arnaud ; Evans, Robin

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Melbourne Univ., Vic., Australia
  • Volume
    6
  • fYear
    2003
  • fDate
    9-12 Dec. 2003
  • Firstpage
    6313
  • Abstract
    A maneuvering target is to be tracked based on noise corrupted measurements of the target´s state that are received by a moving observer. Additionally, the quality of the target state observations can be improved by the appropriate positioning of the observer relative to the target during tracking. The bearings-only tracking problem is an example of this scenario. The question of optimal observer trajectory planning naturally arises, i.e. how should the observer maneuver relative to the target in order to optimise the tracking performance? In this paper, we formulate this problem as a discrete-time stochastic optimal control problem and present a novel stochastic approximation algorithm for designing the observer trajectory. Numerical examples are presented to demonstrate the utility of the proposed methodology.
  • Keywords
    approximation theory; discrete time systems; observers; optimal control; path planning; stochastic systems; target tracking; discrete-time stochastic optimal control; maneuvering target; optimal observer trajectory planning; stochastic approximation; Approximation algorithms; Artificial intelligence; Electric variables measurement; Equations; Noise measurement; Observers; Signal processing; Stochastic processes; Target tracking; Trajectory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control, 2003. Proceedings. 42nd IEEE Conference on
  • ISSN
    0191-2216
  • Print_ISBN
    0-7803-7924-1
  • Type

    conf

  • DOI
    10.1109/CDC.2003.1272313
  • Filename
    1272313