• DocumentCode
    1623247
  • Title

    Extended Kalman particle filter angle tracking (EKPF-AT) algorithm for tracking multiple targets

  • Author

    Hou, Sheng-Yun ; Hung, Hsien-Sen ; Kao, Tsai-Sheng

  • Author_Institution
    Dept. of Electron. Eng., Hwa Hsia Inst. of Technol., Taipei, Taiwan
  • fYear
    2010
  • Firstpage
    216
  • Lastpage
    220
  • Abstract
    In this paper, we present an angle tracking algorithm based on the extended Kalman particle filter (EKPF), called EKPF-AT, using an array of sensors with known locations. This algorithm is capable of determining DOA angles using a single snapshot of data during the interval between each time step. The EKPF combines particle filtering (PF) with the extended Kalman filter (EKF) in order to prevent sample impoverishment during its resampling process. The effectiveness of the proposed algorithm is demonstrated via computer simulations in scenarios involving targets with crossing trajectories.
  • Keywords
    Kalman filters; direction-of-arrival estimation; nonlinear filters; particle filtering (numerical methods); sensor arrays; target tracking; arrival direction angles; extended Kalman particle filter angle tracking algorithm; multiple target tracking; sensor array; angle tracking; direction of arrival (DOA); extended Kalman filter (EKF); particle filter (PF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    System Science and Engineering (ICSSE), 2010 International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-6472-2
  • Type

    conf

  • DOI
    10.1109/ICSSE.2010.5551746
  • Filename
    5551746