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Analog Neural Network Approach for Source Localization Using Time-of-Arrival Measurements

  • Chi-Sing Leung
  • H. C. So
  • Frankie K. W. Chan
  • A. G. Constantinides
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)

Abstract

Source localization can be achieved by making use of the time-of-arrival (TOA) measurements, but it is not a trivial task because the TOAs have nonlinear relationships with the source coordinates. This paper exploits a neural network technique, namely, Lagrange programming neural networks, for TOA-based localization. We also investigate the local stability of our formulation. Simulation results demonstrate that the performance of the proposed location estimator approaches the optimality benchmark of Cram\({\rm\acute{e}}\)r-Rao lower bound.

Keywords

Analog network source localization time-of-arrival 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Chi-Sing Leung
    • 1
  • H. C. So
    • 1
  • Frankie K. W. Chan
    • 1
  • A. G. Constantinides
    • 2
  1. 1.Dept. of Electronic EngineeringCity University of Hong KongHong Kong
  2. 2.Imperial CollegeUK

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