• DocumentCode
    3595530
  • Title

    Robust TOA based localization for wireless sensor networks with anchor position uncertainties

  • Author

    Mekonnen, Zemene Walle ; Wittneben, Armin

  • Author_Institution
    Commun. Technol. Lab., ETH Zurich, Zurich, Switzerland
  • fYear
    2014
  • Firstpage
    2029
  • Lastpage
    2033
  • Abstract
    In this paper, we address the problem of sensor network localization based on Time-of-Arrival (TOA) measurements under the presence of anchor location errors. We consider the practically appealing setup where the agents are low-complexity transmit-only nodes whose clocks´ are not synchronized with that of the anchors. The maximum likelihood (ML) solution of the localization problem is formulated and shown to be a non-convex optimization problem. The relaxation of the ML solution to a convex optimization problem based on semi-definite programming (SDP) is proposed. The proposed localization method is compared with the Cramér Rao lower bound (CRLB) and an existing related approach. Simulation results show that the proposed localization method outperforms the existing scheme, notably when the anchor location uncertainties are the dominant source of errors.
  • Keywords
    concave programming; maximum likelihood estimation; sensor placement; time-of-arrival estimation; wireless sensor networks; Cramér Rao lower bound; ML solution; TOA measurements; anchor location errors; anchor position uncertainties; low-complexity transmit-only nodes; maximum likelihood solution; nonconvex optimization problem; semidefinite programming; sensor network localization; time-of-arrival measurements; wireless sensor networks; Clocks; Convex functions; Distance measurement; Maximum likelihood estimation; Measurement errors; Synchronization; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Personal, Indoor, and Mobile Radio Communication (PIMRC), 2014 IEEE 25th Annual International Symposium on
  • Type

    conf

  • DOI
    10.1109/PIMRC.2014.7136505
  • Filename
    7136505