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.

• Record URL:
  http://www2.cmu-edu.eu/annals/on-line-journal/
• 
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/15823601
• Supplemental Notes:
  • Abstract used by permission of publisher.
• Authors:
  • Dalina, Zevedei
  • Mariana, Jurian
  • Adrian, Sabau
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References;
• Pagination: pp 193-196
• Serial:
  • Constanta Maritime University Annals
  • Volume: 17
  • Publisher: Constanta Maritime University
  • ISSN: 1582-3601
  • Serial URL: https://cmu-edu.eu/annals/

Subject/Index Terms

• TRT Terms: Algorithms; Kalman filtering; Networks; Sensors; Tracking systems; Wireless communication systems
• Identifier Terms: MATLAB (Computer program)
• Subject Areas: Administration and Management; Data and Information Technology; Transportation (General); I10: Economics and Administration;

Filing Info

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