A novel real time method of signal strength based indoor localization

Letian Ye, Zhi Geng, Lingzhou Xue, Zhihai Liu

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

2 Citations (Scopus)

Abstract

Localization using wireless signal is a hot field now, and the real time indoor localization is a difficult problem for its complex and sensitive to the environment. This paper proposes a method based on grid to convert global to local. Based on the Markov random field, we convert efficiently signals between different environments and achieve high precision and fast speed. The paper also discusses influence of multiple signals to location precision, explains that multiple sets of signal can be used greatly to improve localization precision. To reduce the number of supervised grids in learning data required by the grid-matching algorithm, this paper presents a method which combines the grid matching and the signal strength model. First the position is localized by the grid-matching method and then its location is refined by using the signal strength model in the local area.

Original languageEnglish (US)
Title of host publicationComputational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings
Pages678-688
Number of pages11
EditionPART 1
StatePublished - Dec 1 2007
EventInternational Conference on Computational Science and its Applications, ICCSA 2007 - Kuala Lumpur, Malaysia
Duration: Aug 26 2007Aug 29 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4705 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherInternational Conference on Computational Science and its Applications, ICCSA 2007
CountryMalaysia
CityKuala Lumpur
Period8/26/078/29/07

Fingerprint

Grid
Convert
Matching Algorithm
Random Field
Model

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Ye, L., Geng, Z., Xue, L., & Liu, Z. (2007). A novel real time method of signal strength based indoor localization. In Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings (PART 1 ed., pp. 678-688). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4705 LNCS, No. PART 1).
Ye, Letian ; Geng, Zhi ; Xue, Lingzhou ; Liu, Zhihai. / A novel real time method of signal strength based indoor localization. Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 1. ed. 2007. pp. 678-688 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).
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Ye, L, Geng, Z, Xue, L & Liu, Z 2007, A novel real time method of signal strength based indoor localization. in Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4705 LNCS, pp. 678-688, International Conference on Computational Science and its Applications, ICCSA 2007, Kuala Lumpur, Malaysia, 8/26/07.

A novel real time method of signal strength based indoor localization. / Ye, Letian; Geng, Zhi; Xue, Lingzhou; Liu, Zhihai.

Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 1. ed. 2007. p. 678-688 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4705 LNCS, No. PART 1).

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

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AB - Localization using wireless signal is a hot field now, and the real time indoor localization is a difficult problem for its complex and sensitive to the environment. This paper proposes a method based on grid to convert global to local. Based on the Markov random field, we convert efficiently signals between different environments and achieve high precision and fast speed. The paper also discusses influence of multiple signals to location precision, explains that multiple sets of signal can be used greatly to improve localization precision. To reduce the number of supervised grids in learning data required by the grid-matching algorithm, this paper presents a method which combines the grid matching and the signal strength model. First the position is localized by the grid-matching method and then its location is refined by using the signal strength model in the local area.

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Ye L, Geng Z, Xue L, Liu Z. A novel real time method of signal strength based indoor localization. In Computational Science and Its Applications - ICCSA 2007 - International Conference, Proceedings. PART 1 ed. 2007. p. 678-688. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).