• DocumentCode
    646068
  • Title

    Radar resource management: Dynamic programming and dynamic finite state machines

  • Author

    Jinwoo Seok ; Jinxin Zhao ; Selvakumar, Jhanani ; Sanjaya, Edwin ; Kabamba, Pierre T. ; Girard, Antoine

  • Author_Institution
    Dept. of Aerosp. Eng., Univ. of Michigan, Ann Arbor, MI, USA
  • fYear
    2013
  • fDate
    17-19 July 2013
  • Firstpage
    4100
  • Lastpage
    4105
  • Abstract
    Finite state machines are a standard tool to model event-based control logic, and dynamic programming is a staple of optimal decision-making. We combine these approaches in the context of radar resource management for Naval surface warfare. There is a friendly (Blue) force in the open sea, equipped with one multi-function radar and multiple ships. The enemy (Red) force consists of missiles that target the Blue force´s radar. The mission of the Blue force is to foil the enemy´s threat by careful allocation of radar resources. Dynamically composed finite state machines are used to formalize the model of the battle space and dynamic programming is applied to our dynamic state machine model to generate an optimal policy. To achieve this in near-real-time and a changing environment, we use approximate dynamic programming methods. Example scenario illustrating the model and simulation results are presented.
  • Keywords
    dynamic programming; finite state machines; marine radar; military radar; ships; battle space; dynamic finite state machine; dynamic programming; dynamic state machine model; event based control logic; finite state machines; multifunction radar; naval surface warfare; optimal decision making; optimal policy; radar resource management; Computational modeling; Dynamic programming; Force; Marine vehicles; Missiles; Radar detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (ECC), 2013 European
  • Conference_Location
    Zurich
  • Type

    conf

  • Filename
    6669470