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 publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages180-195
Number of pages16
Volume3868 LNCS
DOIs
Publication statusPublished - 2006
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)03029743
ISSN (Electronic)16113349

Other

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

Fingerprint

Tessellation
Delaunay
Global positioning system
Vertex of a graph
Acoustics
Sensor nodes
Sensor networks
Equipment and Supplies
Hierarchical Networks
Field Experiment
Experiments
Sensor Networks
Receiver
Sensor
Children

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3868 LNCS, 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

Hierarchical localization algorithm based on inverse delaunay tessellation. / Saeki, Masayuki; Inoue, Junya; Khor, Kok How; Kousaka, Tomohiro; Honda, Hiroaki; Oguni, Kenji; Hori, Muneo.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3868 LNCS 2006. p. 180-195 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3868 LNCS).

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

Saeki, M, Inoue, J, Khor, KH, Kousaka, T, Honda, H, Oguni, K & Hori, M 2006, Hierarchical localization algorithm based on inverse delaunay tessellation. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3868 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3868 LNCS, pp. 180-195, 3rd European Workshop on Wireless Sensor Networks, EWSN 2006, Zurich, Switzerland, 06/2/13. https://doi.org/10.1007/11669463_15
Saeki M, Inoue J, Khor KH, Kousaka T, Honda H, Oguni K et al. Hierarchical localization algorithm based on inverse delaunay tessellation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3868 LNCS. 2006. p. 180-195. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11669463_15
Saeki, Masayuki ; Inoue, Junya ; Khor, Kok How ; Kousaka, Tomohiro ; Honda, Hiroaki ; Oguni, Kenji ; Hori, Muneo. / Hierarchical localization algorithm based on inverse delaunay tessellation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3868 LNCS 2006. pp. 180-195 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{c684eba94d3849389726b0cdea2aced1,
title = "Hierarchical localization algorithm based on inverse delaunay tessellation",
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).",
author = "Masayuki Saeki and Junya Inoue and Khor, {Kok How} and Tomohiro Kousaka and Hiroaki Honda and Kenji Oguni and Muneo Hori",
year = "2006",
doi = "10.1007/11669463_15",
language = "English",
isbn = "3540321586",
volume = "3868 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "180--195",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Hierarchical localization algorithm based on inverse delaunay tessellation

AU - Saeki, Masayuki

AU - Inoue, Junya

AU - Khor, Kok How

AU - Kousaka, Tomohiro

AU - Honda, Hiroaki

AU - Oguni, Kenji

AU - Hori, Muneo

PY - 2006

Y1 - 2006

N2 - 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).

AB - 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).

UR - http://www.scopus.com/inward/record.url?scp=33745546892&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33745546892&partnerID=8YFLogxK

U2 - 10.1007/11669463_15

DO - 10.1007/11669463_15

M3 - Conference contribution

AN - SCOPUS:33745546892

SN - 3540321586

SN - 9783540321583

VL - 3868 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 180

EP - 195

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -