• DocumentCode
    1717185
  • Title

    Applied research of location fingerprint positioning system based on the improved AUKF algorithm

  • Author

    Cao Chunping ; Chen Ping ; Wang Yagang

  • Author_Institution
    Sch. of Opt.-Electr. & Comput. Eng., Univ. of Shanghai for Sci. & Technol., Shanghai, China
  • fYear
    2013
  • Firstpage
    4023
  • Lastpage
    4027
  • Abstract
    Because of the signal error existing in mine personnel positioning when using location fingerprint positioning, the paper proposes self-adaptive unscented Kalman filter (Adaptive UKF, AUKF) algorithm. The filtering algorithm can actively suppress signal diverging and compensate for the signal loss brought about by the noise, and further improve the accuracy of the sample signal in location fingerprint positioning method. By associating the accurate signal positioning with the position algorithm, the system can obtain more accurate target location.
  • Keywords
    Kalman filters; fingerprint identification; improved AUKF algorithm; location fingerprint positioning system; position algorithm; sample signal accuracy; self-adaptive unscented Kalman filter algorithm; signal diverging suppression; signal loss compensation; Adaptive optics; Educational institutions; Electronic mail; Fingerprint recognition; Kalman filters; Optical computing; Optical filters; Adaptive Unscented Kalman Filter; location fingerprint positioning; real-time tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Conference (CCC), 2013 32nd Chinese
  • Conference_Location
    Xi´an
  • Type

    conf

  • Filename
    6640124