Physical-layered System

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2007.04
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Outline

• General Description
• Breakthroughs and Major Achievements
• Categorized Summary
• A Summary of the Post-Project Plan
• International Cooperation Activities

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General Description (1/2)
Decentralized Positioning Schemes for WSNs

• Motivation
• With the rapid increase in wireless
  communications, location-aware services have
  received a great deal of attention for
  commercial, public-safety, and military
  applications.

• Location Estimators for Indoor WLANs
• Frameworks of the location system
• Experimental results
• More than 90 percent of the estimated locations
  using the proposed location estimator have error
  distances less than 2.3 meters

• Goal
• Developing more effective, accurate, and robust
  positioning methods for wireless networks

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General Description (2/2)
Decentralized Positioning Schemes for WSNs

• Weighted Interpolation (WIP) Method

• Client-Based-Like Location Estimator
  (Tracking-Assisted)
• MNs report the joint location information from a
  decentralized scheme
• Simulation results
• Based on the path-loss model
• More than 90 percent of the estimated locations
  using the proposed location estimator have error
  distances less than 2.5 meters

• The Trajectory of an Mobile Node (MN) based on
  the WIP Method

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Breakthroughs and Major Achievements (1/2)

• Wireless Sensor Networks

Technology State-of-the-Art Breakthrough
A Decentralized Positioning Method Using Combined the Weighted Interpolation (WIP) with Tracking Algorithms for Wireless Sensor Networks Sensor network source localization via projection onto convex sets (POCS). (A. O. Hero and D. Blatt, University of Michigan, Ann Arbor ) The reliability of the sensors are considered when the sensors compute the global estimate of the location of target location. By employing tracking algorithms at the central server, the simulation results demonstrate that more than 90 percent of the estimated locations using the method have error distances less than 2.5 meters, while the POCS method achieved error distances more than 5.2 meters.
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Breakthroughs and Major Achievements (2/2)

• Wireless Location-Estimation Technologies for
  Indoor WLANs (70)
• Location Estimation Using Calibrating
• SNR-Based Location Estimation Using Combined
  Radio Propagation Modeling and Adaptive Kalman
  Filtering
• Wireless Location-Estimation Technologies for
  WSNs (30)
• A Decentralized Positioning Method Based on
  Weighted Interpolation
• An Adaptive Location Estimator Based on tracking
  algorithms

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Categorized Summary (1/2)
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Categorized Summary (2/2)

• Conference papers (2006/4/1 2007/03/31)
• C.-L. Wang, Y.-W. Hong, and Y.-S. Dai, "A
  decentralized positioning method for wireless
  sensor networks based on weighted interpolation,"
  accepted for presentation in the 2007 IEEE
  International Conference on Communications
  (ICC2007), Glasgow, Scotland, June 2007.
• C.-L. Wang, Y.-S. Chiou, and Y.-S. Dai, "An
  adaptive location estimator based on Kalman
  filtering for wireless sensor networks," accepted
  for presentation in the 2007 IEEE Vehicular
  Technology Conference - Spring (VTC2007-Spring),
  Dublin, Ireland, April 2007.
• C.-L. Wang, Y.-S. Chiou, and Y.-S. Dai, "An
  adaptive location estimator based on alpha-beta
  filtering for wireless sensor networks," in
  Proceedings of the 2007 IEEE Wireless
  Communications and Networking Conference
  (WCNC2007), Hong Kong, March 2007.
• Y.-S. Chiou, C.-L. Wang, and S.-C. Yeh, "An
  adaptive location estimator based on Kalman
  filtering for indoor dynamic environments," in
  Proceedings of the 2006 IEEE Vehicular Technology
  Conference - Fall (VTC2006-Fall), Montreal,
  Canada, Sept. 2006.
• C.-L. Wang and Y.-S. Chiou, "An adaptive
  positioning scheme based on radio propagation
  modeling for indoor WLANs," in Proceedings of the
  2006 IEEE Vehicular Technology Conference -
  Spring (VTC2006-Spring), Melbourne, Australia,
  May 2006.

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A Summary of the Post-Project Plan
Technology 200-2004 2005-2006 2007-2008
Wireless location-estimation Technologies Location estimators for Indoor WLANs Signal processing, positioning, and tracking techniques for WLANs Location estimators based on signal processing, positioning, and tracking techniques for WSNs