• DocumentCode
    437584
  • Title

    Reconfigurable Bayesian networks for adaptive situation assessment in battlespace

  • Author

    Mirmoeini, Farnoush ; Krishnamurthy, Vikram

  • Author_Institution
    Dept. of Electr. & Comput. Eng., British Columbia Univ., Vancouver, BC, Canada
  • fYear
    2005
  • fDate
    19-22 March 2005
  • Firstpage
    810
  • Lastpage
    815
  • Abstract
    Situation assessment is the task of integrating low-level sensor data to fuse lower level information and produce hypotheses in a military situation. In this paper we propose an algorithm for adaptive situation assessment using reconfigurable Bayesian networks. The formulation and algorithm presented are suitable for dynamic battlespace situation changes. We provide numerical examples that show the effectiveness of our approach in a battlefield scenario.
  • Keywords
    belief networks; military computing; adaptive situation assessment; battlefield scenario; dynamic battlespace situation changes; low-level sensor data; lower level information; military situation; reconfigurable Bayesian networks; Adaptive systems; Bayesian methods; Fuses; Inference algorithms; Information systems; Intelligent networks; Level control; Maximum likelihood estimation; Military computing; Sensor phenomena and characterization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control, 2005. Proceedings. 2005 IEEE
  • Print_ISBN
    0-7803-8812-7
  • Type

    conf

  • DOI
    10.1109/ICNSC.2005.1461294
  • Filename
    1461294