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A fast data fusion algorithm based on matrix analysis for target recognition in sensor networks

  • Quanlong Li*
  • , Xiaofei Xu
  • , Qingjun Yan
  • , Zhaobo Wang
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Data fusion always be used to solve the problem of target recognition in wireless sensor networks, and Dempster-Shafer inference have been proven one of effective methods. However, the high computation complexity of D-S evidence combination usually prevent it to be used in low ability sensor networks directly, especially it may violate the requirements for real-time processing and synchronization of sensor networks. To increase the speed of target recognition in wireless sensor networks, a fast data fusion algorithm based on matrix analysis is proposed in this paper, which inherits the idea of D-S evidence theory. The algorithm holds the same recognition capability as D-S evidence combination formula, but reduces time complexity. This conclusion has been confirmed by simulation.

Original languageEnglish
Title of host publicationProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Pages468-474
Number of pages7
DOIs
StatePublished - 2010
Externally publishedYes
Event1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 - Harbin, China
Duration: 17 Sep 201019 Sep 2010

Publication series

NameProceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010

Conference

Conference1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010
Country/TerritoryChina
CityHarbin
Period17/09/1019/09/10

Keywords

  • Data fusion
  • Evidence theory
  • Matrix analysis
  • Sensor network
  • Target recognition

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