• DocumentCode
    1794940
  • Title

    Particle filter based joint tracking and classification

  • Author

    Kun Zhan ; Long Xu ; Hong Jiang ; Liang Bai ; Mengjie Wu

  • Author_Institution
    Sci. & Technol. on Aircraft Control Lab., Beihang Univ., Beijing, China
  • fYear
    2014
  • fDate
    8-10 Aug. 2014
  • Firstpage
    762
  • Lastpage
    766
  • Abstract
    To overcome the high computational complexity of the existing joint tracking and classification (JTC) algorithm, particle filter (PF) is introduced to replace numerical integration in solving JTC, and hence computational load is considerably reduced. Our particle filter based JTC (PF-JTC) algorithm makes use of the target kinematic information provided by the low-resolution radar (LLR) and the target electromagnetic equipment information provided by the electronic support measure (ESM) to improve the performance of tracking and classification simultaneously. Simulation results verify the effectiveness of the proposed PF-JTC algorithm.
  • Keywords
    particle filtering (numerical methods); radar signal processing; signal classification; target tracking; ESM; LLR; PF-JTC algorithm; electromagnetic equipment information; electronic support measure; kinematic information; low-resolution radar; particle filter based joint tracking and classification; Classification algorithms; Joints; Particle filters; Radar tracking; Sensor phenomena and characterization; Target tracking; electronic support measure (ESM); joint tracking and classification (JTC); low-resolution radar (LRR); particle filter (PF); particle filter based JTC (PF-JTC);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE Chinese
  • Conference_Location
    Yantai
  • Print_ISBN
    978-1-4799-4700-3
  • Type

    conf

  • DOI
    10.1109/CGNCC.2014.7007307
  • Filename
    7007307