Application of Bayesian Algorithms in Localization and Tracking of Moving Devices in WSNs

Localization of moving devices (MD) plays an essential role in wireless sensor networks (WSN). Most of WSN applications need the knowledge of the node’s location. Localization algorithms with high accuracy and low complexity are very important for WSN. This paper focuses on mobile wireless sensor networks localization techniques based on Bayesian method and target tracking based on Extended Kalman filter and particle filter algorithm (PF). The properties of Extended Kalman Filter (EKF) and particle filter (PF) are described, simulated on MATLAB and analyzed. Then their performance are compared from the aspects of localization accuracy and sample number.

Language

  • English

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Filing Info

  • Accession Number: 01482017
  • Record Type: Publication
  • Files: TRIS
  • Created Date: May 9 2013 3:08PM