IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v13y2017i4p1550147717703115.html
   My bibliography  Save this article

ASMT: An augmented state-based multi-target tracking algorithm in wireless sensor networks

Author

Listed:
  • Kejiang Xiao
  • Rui Wang
  • Lei Zhang
  • Jian Li
  • Tun Fun

Abstract

Due to the resource limitation and low performance of sensor node, research works of multi-target tracking became a hot spot in the applications of wireless sensor networks. Here, we propose an algorithm named augmented state-based multi-target tracking algorithm. To augment the state of the target tracking, augmented state-based multi-target tracking algorithm can effectively reduce the computational complexity of data association. Then, multi-target tracking in wireless sensor networks can be implemented by augmented state-based multi-target tracking algorithm as a simplified Bayesian estimation method is adopted. The simulation of multi-target tracking in wireless sensor networks demonstrates that augmented state-based multi-target tracking algorithm has less computation and higher accuracy than traditional method, especially in the implementation of maneuvering targets with intersection.

Suggested Citation

  • Kejiang Xiao & Rui Wang & Lei Zhang & Jian Li & Tun Fun, 2017. "ASMT: An augmented state-based multi-target tracking algorithm in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 13(4), pages 15501477177, April.
    • Handle: RePEc:sae:intdis:v:13:y:2017:i:4:p:1550147717703115
    DOI: 10.1177/1550147717703115
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147717703115
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1550147717703115?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:intdis:v:13:y:2017:i:4:p:1550147717703115. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.