TY - JOUR

T1 - Bridging gap between multi-dimensional scaling-based and optimum network localisation via efficient refinement

AU - Zhu, S.

AU - Ding, Z.

PY - 2012/4

Y1 - 2012/4

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84860867276&partnerID=8YFLogxK

U2 - 10.1049/iet-spr.2010.0352

DO - 10.1049/iet-spr.2010.0352

M3 - Article

AN - SCOPUS:84860867276

SN - 1751-9675

VL - 6

SP - 132

EP - 142

JO - IET Signal Processing

JF - IET Signal Processing

IS - 2

ER -