A supplement to multidimensional scaling framework formobile location: a unified view
IEEE Transactions on Signal Processing
Efficient weighted multidimensional scaling for wireless sensor network localization
IEEE Transactions on Signal Processing
Ranging energy optimization for robust sensor positioning based on semidefinite programming
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Distributed Push-pull Estimation for node localization in wireless sensor networks
Journal of Parallel and Distributed Computing
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Recently, multidimensional scaling (MDS) algorithms have been verified to be robust for the mobile localization. However, they do not achieve the Cramer-Rao lower bound (CRLB), even though the measurement noise is small. In this paper, a novel weighted MDS method is proposed for time-of-arrival based mobile location. It can achieve the CRLB at moderate noise level before the threshold effect occurs. In addition, unlike the classical MDS methods depending on the eigendecomposition of the scalar product matrix, the proposed method is based on the matrix itself directly, which in turn decreases the computational complexity.