• DocumentCode
    1478257
  • Title

    Cooperative Localization and Tracking of Mobile Ad Hoc Networks

  • Author

    Dong, Liang

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Baylor Univ., Waco, TX, USA
  • Volume
    60
  • Issue
    7
  • fYear
    2012
  • fDate
    7/1/2012 12:00:00 AM
  • Firstpage
    3907
  • Lastpage
    3913
  • Abstract
    Cooperative localization and tracking technique relies on pairwise measurements to jointly estimate the positions and the velocities of multiple nodes in a mobile ad hoc network. The pairwise measurements include the range and the radial velocity between the transmitting and receiving nodes. For a large-scale network, we formulate the state-space models for the subsystems and develop the distributed extended Kalman filters for cooperative localization and tracking. The decentralized approach takes into account the limited resources of node memory, embedded computation, and communication bandwidth. The algorithm works well in a sparsely connected mobile network and can adapt to changes in network connectivity. Numerical results show that the performances of the decentralized cooperative localization and node velocity estimation are close to the posterior Cramér-Rao lower bounds of the centralized approach.
  • Keywords
    Kalman filters; cooperative communication; distributed algorithms; measurement systems; mobile ad hoc networks; nonlinear filters; radio receivers; radio transmitters; state-space methods; tracking; communication bandwidth; cooperative tracking; decentralized cooperative localization; distributed extended Kalman filters; embedded computation; large-scale network; mobile ad hoc networks; node memory; node velocity estimation; pairwise measurements; posterior Cramer-Rao lower bounds; radial velocity; receiving nodes; sparsely connected mobile network; state-space models; transmitting nodes; Kalman filters; Mobile ad hoc networks; Mobile communication; Noise; State-space methods; Vectors; Velocity measurement; Adaptive signal processing; Kalman filters; cooperative systems; distributed algorithms; estimation theory; mobile ad hoc networks;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2012.2191778
  • Filename
    6174479