Nonmetric MDS for sensor localization

被引：16

作者：

Nhat, Vo Dinh Minh ^{[1
]}

Vo, Duc ^{[2
]}

Challa, Subhash ^{[1
]}

Lee, SungYoung ^{[3
]}

机构：

[1] Univ Melbourne, Victorian Res Lab, Melbourne, Vic 3010, Australia

[2] Univ Technol, Victorian Res Lab, Sydney, NSW, Australia

[3] Kyung Hee Univ, Ubiquitous Comp Lab, Dongdaemun gu, South Korea

来源：

2008 3RD INTERNATIONAL SYMPOSIUM ON WIRELESS PERVASIVE COMPUTING, VOLS 1-2 | 2008年

关键词：

D O I：

10.1109/ISWPC.2008.4556237

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Multidimensional Scaling (MDS) has been recently applied to node localization in sensor networks and gained some very impressive performance. MDS treats dissimilarities of pair-wise nodes directly as Euclidean distances and then makes use of the spectral decomposition of a doubly centered matrix of dissimilarities. However dissimilarities mainly estimated by Received Signal Strength (RSS) or by the Time of Arrival (TOA) of communication signal from the sender to the receiver used to suffer errors. From this observation, Nonmetric Multidimensional Scaling (NMDS) based only the rank order of the dissimilarities is proposed in this paper. Different from MDS, NMDS obtain insights into the nature of "perceived" dissimilarities which makes it more suitable to the problem of sensor localization. The experiment on real sensor network measurements of RSS and TOA shows the efficiency and novelty of NMDS for sensor localization problem in term of sensor location-estimated error.

引用

页码：396 / +

页数：2

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