Quantitative uncertainty-based incremental localization and anchor selection in wireless sensor networks

Zhiheng Xie, Mingyi Hong, Hengchang Liu, Jingyuan Li, Kangyuan Zhu, John A.stankovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Previous localization solutions in wireless sensor networks mainly focus on using various techniques to estimate node positions. In this paper, we argue that quantifying the uncertainty of these estimates is equally important in practice. By using the quantitative uncertainty of measurements and estimates, we can derive more accurate estimates by better fusing the measurements, provide confidence information for confidence-based applications, and know how to select the best anchor nodes so as to minimize the total mean square errors of the whole network. This paper quantifies the estimation uncertainty as an error covariance matrix, and presents an efficient incremental centralized algorithm-INOVA and a decentralized algorithm-OSE-COV for calculating the error covariance matrix. Furthermore, we present how to use the error covariance matrix to infer the confidence region of each node's estimate, and provide an optimal strategy for the anchor selection problem. Extensive simulation results show that INOVA significantly improves the computation efficiency when the network changes dynamically; the confidence region inference is accurate when the measurement number to node number ratio is more than 2; and the optimal anchor selection strategy reduces the total mean square error by four times as much as the variation-based algorithm in best case.

Original languageEnglish (US)
Title of host publicationMSWiM'11 - Proceedings of the 14th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems
Pages417-426
Number of pages10
DOIs
StatePublished - Dec 13 2011
Event14th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM'11 - Miami, FL, United States
Duration: Oct 31 2011Nov 4 2011

Publication series

NameMSWiM'11 - Proceedings of the 14th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems

Other

Other14th ACM International Conference on Modeling, Analysis, and Simulation of Wireless and Mobile Systems, MSWiM'11
CountryUnited States
CityMiami, FL
Period10/31/1111/4/11

Keywords

  • Localization
  • Uncertainty
  • Wireless sensor network

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