Hierarchical localization algorithm based on inverse delaunay tessellation

Masayuki Saeki, Junya Inoue, Kok How Khor, Tomohiro Kousaka, Hiroaki Honda, Kenji Oguni, Muneo Hori

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

1 Citation (Scopus)

Abstract

This paper presents the hierarchical sensor network system for robust localization. This system consists of parent nodes with a low priced LI GPS receiver and child nodes equipped with an acoustic ranging device. Relative positions between child nodes are estimated based on acoustic ranging through the inverse Delaunay algorithm. This algorithm localizes all the nodes simultaneously, thus, the accumulation of the error in the localization is suppressed. Relatively localized child sensor nodes are given global coordinates with the help of GPS on parent nodes. Field experiment was conducted with three GPS parent nodes and twenty-one child nodes (MOTE).

Original languageEnglish
Title of host publicationWireless Sensor Networks - Third European Workshop, EWSN 2006, Proceedings
Pages180-195
Number of pages16
DOIs
Publication statusPublished - 2006 Jul 7
Externally publishedYes
Event3rd European Workshop on Wireless Sensor Networks, EWSN 2006 - Zurich, Switzerland
Duration: 2006 Feb 132006 Feb 15

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3868 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other3rd European Workshop on Wireless Sensor Networks, EWSN 2006
CountrySwitzerland
CityZurich
Period06/2/1306/2/15

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Saeki, M., Inoue, J., Khor, K. H., Kousaka, T., Honda, H., Oguni, K., & Hori, M. (2006). Hierarchical localization algorithm based on inverse delaunay tessellation. In Wireless Sensor Networks - Third European Workshop, EWSN 2006, Proceedings (pp. 180-195). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3868 LNCS). https://doi.org/10.1007/11669463_15