A novel node localization algorithm for anisotropic wireless sensor networks with holes based on MDS-MAP and EKF

Shi Zhang, Baihai Zhang, Meng Joo Er, Zixiao Guan

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

9 Citations (Scopus)

Abstract

The node localization technique is the basis of applications of the wireless sensor networks (WSNs). The existence of holes will affect the shortest distance between nodes and result in low accuracy of node localization. In this paper, an Extended Kalman Filter Multidimensional Scaling (EKF-MDS) localization algorithm is proposed. By exploring the virtual node and constructing the shortest paths between nodes, the Euclidean distances between nodes are obtained. The Extended Kalman Filter (EKF) is applied to refine the localized coordinates which are obtained by the MDS-MAP algorithm. Simulation results demonstrate that the proposed algorithm is exceedingly accurate and efficient comparing to state-of-the-art methods in anisotropic networks with holes.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3022-3025
Number of pages4
ISBN (Electronic)9781509025961
DOIs
Publication statusPublished - 8 Feb 2017
Event2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore
Duration: 22 Nov 201625 Nov 2016

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2016 IEEE Region 10 Conference, TENCON 2016
Country/TerritorySingapore
CitySingapore
Period22/11/1625/11/16

Keywords

  • anisotropic networks
  • extended kalman filter
  • node localization
  • wireless sensor networks

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