• DocumentCode
    3275504
  • Title

    Multi-sensor management: Optimal allocation of tracking resources for Pd < 1 based on the interacting multiple model modified kalman filter

  • Author

    Jun, Tong ; Shan Gan-lin

  • Author_Institution
    Dept. of Opt. & Electron. Eng., Coll. of Mech. Eng., Shijiazhuang, China
  • fYear
    2011
  • fDate
    15-17 April 2011
  • Firstpage
    532
  • Lastpage
    535
  • Abstract
    This paper presents a novel sensor selection algorithm for optimal allocation of target tracking resources, based on the interacting multiple model modified kalman filter. The algorithm can be easily calculated and it is possible to include sensors with a probability of detection Pd <;1. The sensor selection measure function is the minimum trace of covariance matrix. The performance of the sensor selection algorithm is studied for single sensor and sensor collocation. And simulation shows the method is effective and feasible.
  • Keywords
    Kalman filters; covariance matrices; probability; resource allocation; sensor fusion; target tracking; covariance matrix; detection probability; interacting multiple model modified Kalman filter; multisensor management; optimal target tracking resource allocation; sensor collocation; sensor selection algorithm; Covariance matrix; Kalman filters; Mathematical model; Optimization; Radar tracking; Target tracking; IMMMKF; measure function; multi-sensor management; sensor selection; trace;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Information and Control Engineering (ICEICE), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-8036-4
  • Type

    conf

  • DOI
    10.1109/ICEICE.2011.5777375
  • Filename
    5777375