Efficient weighted multidimensional scaling for wireless sensor network localization

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Pages (from-to)4548-4553
Journal / PublicationIEEE Transactions on Signal Processing
Volume57
Issue number11
Publication statusPublished - 2009

Abstract

Localization of sensor nodes is a fundamental and important problem in wireless sensor networks. Although classical multidimensional scaling (MDS) is a computationally attractive positioning method, it is statistically inefficient and cannot be applied in partially-connected sensor networks. In this correspondence, a weighted MDS algorithm is devised to circumvent these limitations. It is proved that the estimation performance of the proposed algorithm can attain Cramér-Rao lower bound (CRLB) for sufficiently small noise conditions. Computer simulations are included to contrast the performance of the proposed algorithm with the classical MDS and distributed weighted MDS algorithms as well as CRLB. © 2009 IEEE.

Research Area(s)

  • Localization, Multidimensional scaling, Wireless sensor networks