• DocumentCode
    2477154
  • Title

    Moving targets tracking and observing in a distributed mobile sensor network

  • Author

    La, Hung M. ; Sheng, Weihua

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Oklahoma State Univ., Stillwater, OK, USA
  • fYear
    2009
  • fDate
    10-12 June 2009
  • Firstpage
    3319
  • Lastpage
    3324
  • Abstract
    Tracking and observing multiple dynamic targets is an important task in mobile sensor networks. This paper presents a novel approach to the problem of sensor splitting/ merging for a mobile sensor network to track and observe multiple targets in a dynamic fashion. In this approach, a seed growing graph partition (SGGP) algorithm is proposed to solve the splitting/merging problem. Furthermore, during the process of tracking, collision avoidance and velocity matching among mobile sensors are guaranteed. To demonstrate the benefit of the SGGP algorithm in term of the total energy and time consumption when sensors split, we compare the SGGP with a random selection (RS) algorithm. Numerical experimental tests validate our theoretical results.
  • Keywords
    graph theory; mobile radio; numerical analysis; target tracking; telecommunication congestion control; wireless sensor networks; collision avoidance; distributed mobile sensor network; moving targets tracking; random selection algorithm; seed growing graph partition algorithm; sensor splitting-merging problem; velocity matching; Algorithm design and analysis; Communication system control; Merging; Mobile agents; Mobile computing; Partitioning algorithms; Sensor phenomena and characterization; Target tracking; Vehicle dynamics; Vehicles; Flocking control; Graph partitioning; Mobile sensor network; Multiple targets tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 2009. ACC '09.
  • Conference_Location
    St. Louis, MO
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4244-4523-3
  • Electronic_ISBN
    0743-1619
  • Type

    conf

  • DOI
    10.1109/ACC.2009.5160652
  • Filename
    5160652