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Rethinking of the Uncertainty: A Fault-Tolerant Target-Tracking Strategy Based on Unreliable Sensing in Wireless Sensor Networks

  • Xie, Yi (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Guoming (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Wang, Daifei (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Xiao, Weidong (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Daquan (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology) ;
  • Tang, Jiuyang (Science and Technology Information Systems Engineering Laboratory National University of Defense Technology)
  • Received : 2012.03.09
  • Accepted : 2012.06.14
  • Published : 2012.06.30

Abstract

Uncertainty is ubiquitous in target tracking wireless sensor networks due to environmental noise, randomness of target mobility and other factors. Sensing results are always unreliable. This paper considers unreliability as it occurs in wireless sensor networks and its impact on target-tracking accuracy. Firstly, we map intersection pairwise sensors' uncertain boundaries, which divides the monitor area into faces. Each face has a unique signature vector. For each target localization, a sampling vector is built after multiple grouping samplings determine whether the RSS (Received Signal Strength) for a pairwise nodes' is ordinal or flipped. A Fault-Tolerant Target-Tracking (FTTT) strategy is proposed, which transforms the tracking problem into a vector matching process that increases the tracking flexibility and accuracy while reducing the influence of in-the-filed factors. In addition, a heuristic matching algorithm is introduced to reduce the computational complexity. The fault tolerance of FTTT is also discussed. An extension of FTTT is then proposed by quantifying the pairwise uncertainty to further enhance robustness. Results show FTTT is more flexible, more robust and more accurate than parallel approaches.

Keywords

References

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