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Bridging gap between multi-dimensional scaling-based and optimum network localisation via efficient refinement

Lookup NU author(s): Dr Shouhong Zhu, Dr Zhiguo Ding


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This study deals with the localisation of all nodes in a network, also called as network localisation, based on pairwise distance measurements. The case of a fully connected network is considered, where 'fully connected' refers to that within the whole network every pair of nodes directly connect to each other, thus their pairwise distance can be measured and available. For the localisation of such a network, the multi-dimensional scaling (MDS) algorithm can provide a relative localisation solution, but only a coarse solution when there are measurement errors. To bridge the gap in the localisation performance between the MDS-based and optimum network localisation, the authors propose an efficient subsequent refinement, that is, the iterative least square (LS)/weighted least square (WLS) refinement for the widely existing independent zero-mean Gaussian measurement errors. Analysis and simulation study show that with sufficiently small measurement errors the proposed improved network localisation scheme can achieve, in very limited iterations, the LS/WLS solution, which exhibits the localisation performance the same as the Cramer-Rao lower bound. The authors also extend the proposed refinement to the absolute localisation case with sufficient position-known anchors that are fully and directly connected to all sensors of the network.

Publication metadata

Author(s): Ding Z; Zhu S

Publication type: Article

Publication status: Published

Journal: IET Signal Processing

Year: 2012

Volume: 6

Issue: 2

Pages: 132-142

Print publication date: 14/05/2012

ISSN (print): 1751-9675

ISSN (electronic): 1751-9683

Publisher: Institution of Engineering and Technology


DOI: 10.1049/iet-spr.2010.0352


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Funder referenceFunder name
EP/F062079/1-2UK EPSRC