Abstract
This letter focuses on time-of-arrival based localization using multidimensional similarity (MDS) analysis under non-line-of-sight (NLOS) propagation. To handle row-column structured outliers in the MDS matrix introduced by NLOS errors, we present a novel robust matrix approximation scheme with the use of $\ell _{2,1}$ -norm and apply the alternating direction method of multipliers to solve the resultant nonlinear constrained optimization problem. The proposed method does not require any prior knowledge of NLOS information and can benefit from a comparatively low complexity. Simulation results show that our algorithm is superior to several existing approaches in mild and moderate NLOS environments.
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