Grouping multi-duolateration localization using partial space information for indoor wireless sensor networks

Hojae Lee; Sanghoon Lee; Yeonsoo Kim; Hakjin Chong

doi:10.1109/TCE.2009.5373755

Grouping multi-duolateration localization using partial space information for indoor wireless sensor networks

Hojae Lee, Sanghoon Lee, Yeonsoo Kim, Hakjin Chong

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Article › peer-review

16 Citations (Scopus)

Abstract

Recently, sensor network technologies are being applied to more places such as intelligent home, offices and universities. Localization algorithms are required for indoor wireless sensor network (WSN) applications because the identification of real positions can upgrade the importance of sensing information. In this paper, a sensor network, where small-sized, low-cost and low-rate sensors are uniformly deployed in an indoor WSN environment, is taken into account. We introduce efficient algorithms, termed multiduolateration localization (MDL) and grouping multiduolateration localization (GMDL), which can improve the accuracy of location identification by employing jumper setting. The MDL algorithm can estimate 2-dimensional coordinates with high accuracy by the acquisition of edge information from the setting. In addition, the GMDL algorithm can be applied to the estimation of 3-dimensional coordinates by the acquisition of edge and surface information from the setting. The proposed algorithms perform localization more accurately than trilateration and faster than multidimensional scaling (MDS). The results from a MATLAB simulation show the outperformance of the proposed algorithms and demonstrate the possibility of 3-dimensional localization¹.

Original language	English
Article number	5373755
Pages (from-to)	1950-1958
Number of pages	9
Journal	IEEE Transactions on Consumer Electronics
Volume	55
Issue number	4
DOIs	https://doi.org/10.1109/TCE.2009.5373755
Publication status	Published - 2009 Nov

Bibliographical note

Funding Information:
1This Work was conducted under “KT USN Lab @ Yonsei” Program, Joint R&D Project, of KT Corporation, Korea. “This research was supported by the MKE (Ministry of Knowledge Economy, Korea, under the ITRC(Information Technology Research Center) support program supervised by the IITA(Institute of Information Technology Assessment)” (IITA-2008-C1090-0801-0038) H. J. Lee is with the Dep. of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea (e-mail: hojae84@yonsei.ac.kr). S. H. Lee is with the Dep. of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea (e-mail: slee@yonsei.ac.kr). Y. S. Kim is with the Future Technology Laboratory, KT, Seoul, Korea (e-mail: yeskim@kt.com). H. J. Chong is with the Future Technology Laboratory, KT, Seoul, Korea (e-mail: hjchong@kt.com).

All Science Journal Classification (ASJC) codes

Media Technology
Electrical and Electronic Engineering

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10.1109/TCE.2009.5373755

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title = "Grouping multi-duolateration localization using partial space information for indoor wireless sensor networks",

abstract = "Recently, sensor network technologies are being applied to more places such as intelligent home, offices and universities. Localization algorithms are required for indoor wireless sensor network (WSN) applications because the identification of real positions can upgrade the importance of sensing information. In this paper, a sensor network, where small-sized, low-cost and low-rate sensors are uniformly deployed in an indoor WSN environment, is taken into account. We introduce efficient algorithms, termed multiduolateration localization (MDL) and grouping multiduolateration localization (GMDL), which can improve the accuracy of location identification by employing jumper setting. The MDL algorithm can estimate 2-dimensional coordinates with high accuracy by the acquisition of edge information from the setting. In addition, the GMDL algorithm can be applied to the estimation of 3-dimensional coordinates by the acquisition of edge and surface information from the setting. The proposed algorithms perform localization more accurately than trilateration and faster than multidimensional scaling (MDS). The results from a MATLAB simulation show the outperformance of the proposed algorithms and demonstrate the possibility of 3-dimensional localization1.",

author = "Hojae Lee and Sanghoon Lee and Yeonsoo Kim and Hakjin Chong",

note = "Funding Information: 1This Work was conducted under “KT USN Lab @ Yonsei” Program, Joint R&D Project, of KT Corporation, Korea. “This research was supported by the MKE (Ministry of Knowledge Economy, Korea, under the ITRC(Information Technology Research Center) support program supervised by the IITA(Institute of Information Technology Assessment)” (IITA-2008-C1090-0801-0038) H. J. Lee is with the Dep. of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea (e-mail: hojae84@yonsei.ac.kr). S. H. Lee is with the Dep. of Electrical and Electronics Engineering, Yonsei University, Seoul, Korea (e-mail: slee@yonsei.ac.kr). Y. S. Kim is with the Future Technology Laboratory, KT, Seoul, Korea (e-mail: yeskim@kt.com). H. J. Chong is with the Future Technology Laboratory, KT, Seoul, Korea (e-mail: hjchong@kt.com).",

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N2 - Recently, sensor network technologies are being applied to more places such as intelligent home, offices and universities. Localization algorithms are required for indoor wireless sensor network (WSN) applications because the identification of real positions can upgrade the importance of sensing information. In this paper, a sensor network, where small-sized, low-cost and low-rate sensors are uniformly deployed in an indoor WSN environment, is taken into account. We introduce efficient algorithms, termed multiduolateration localization (MDL) and grouping multiduolateration localization (GMDL), which can improve the accuracy of location identification by employing jumper setting. The MDL algorithm can estimate 2-dimensional coordinates with high accuracy by the acquisition of edge information from the setting. In addition, the GMDL algorithm can be applied to the estimation of 3-dimensional coordinates by the acquisition of edge and surface information from the setting. The proposed algorithms perform localization more accurately than trilateration and faster than multidimensional scaling (MDS). The results from a MATLAB simulation show the outperformance of the proposed algorithms and demonstrate the possibility of 3-dimensional localization1.

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Grouping multi-duolateration localization using partial space information for indoor wireless sensor networks

Abstract

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