• DocumentCode
    3030348
  • Title

    Passive Acoustic Sensor Network Time-Delay Probabilistic Localization Algorithm

  • Author

    Lin, Yuesong ; Wei Du ; Guo, Yunfei

  • Author_Institution
    Inst. of Inf. & Control, Hangzhou Dianzi Univ., Hangzhou, China
  • Volume
    3
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    407
  • Lastpage
    411
  • Abstract
    Target signal is measured by acoustic sensor with the character of time-delay and bearing-only. The problem of target locating and time-delay registration can be solved by composing sensor network. A passive acoustic sensor network time-delay probabilistic localization algorithm is presented in this paper. Firstly, two sensor measures can be chosen that intersection angle is closed to 90° to get initial position of the target. Depend on the initial position, time-delay registration is processed, and then the measure data is refreshed which intersection angle is closed to 90° to get new initial position estimation of the target. Finally, the new initial position is utilized to get more accurate estimation by probabilistic localization algorithm. The simulation results show that the algorithm has the performance of low calculation, real-time and high precision.
  • Keywords
    acoustic transducer arrays; delay estimation; object detection; probability; intersection angle; passive acoustic sensor network; position estimation; target location; time-delay probabilistic localization algorithm; time-delay registration; Acoustic measurements; Acoustic sensors; Acoustic signal detection; Aircraft; Frequency; Position measurement; Radar tracking; Sensor arrays; Sensor phenomena and characterization; Target tracking; acoustic sensor network; bearing-only; probabilistic localization; time-delay;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.275
  • Filename
    5376723