• DocumentCode
    2776674
  • Title

    Cramer-Rao lower bounds for bearings-only maneuvering target tracking with incomplete measurements

  • Author

    Zhigang, Xu ; Andong, Sheng ; Yinya, Li

  • Author_Institution
    Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China
  • fYear
    2009
  • fDate
    17-19 June 2009
  • Firstpage
    2201
  • Lastpage
    2206
  • Abstract
    The theoretical Cramer-Rao lower bound (CRLB) for bearings-only maneuvering target tracking is derived in the case where the observation measurements are lost in a random fashion. Two binary variables are introduced to model two events respectively, one which the target maneuvers or not and another that the target is detected or missed. The corresponding recursive formula for theoretical CRLB is then derived based on the sequential version of the CRLB for general nonlinear systems. The theoretical formula suffers from heavy calculation load of the Fisher information matrix (FIM) while the constant probability of detection is less than unity. An approximation of the theoretical bound is proposed. In addition, a detection reduction factor bound is presented and proved to be less than the theoretical CRLB. The results are illustrated with a numerical example.
  • Keywords
    matrix algebra; nonlinear filters; numerical analysis; probability; signal detection; target tracking; Cramer-Rao lower bounds; Fisher information matrix; bearings-only maneuvering target tracking; detection probability; detection reduction factor bound; general nonlinear systems; numerical example; theoretical formula; Automation; Event detection; Filtering; Linear approximation; Loss measurement; Monte Carlo methods; Nonlinear systems; Probability; Sampling methods; Target tracking; Bearings-only tracking; Cramer-Rao lower bound; Incomplete measurements; Maneuvering target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference, 2009. CCDC '09. Chinese
  • Conference_Location
    Guilin
  • Print_ISBN
    978-1-4244-2722-2
  • Electronic_ISBN
    978-1-4244-2723-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2009.5191603
  • Filename
    5191603