A Novel Weighted Multidimensional Scaling Analysis for Time-of-Arrival-Based Mobile Location

摘要

Recently, multidimensional scaling (MDS) algorithms have been verified to be robust for the mobile localization. However, they do not achieve the CramÉr–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.