Improved Least Median of Squares Localization for Non-Line-of-Sight Mitigation

This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by IEEE-Institute of Electrical and Electronics Engineers and can be found at: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4234©2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Non-line-of-sight (NLOS) propagation is one of the\ud major problems that cause errors in localization systems. There\ud exist many algorithms to reduce NLOS caused errors. Most of\ud these algorithms require a priori information about the NLOS\ud links, which limits their application. Least median of squares\ud (LMedS) method is an exception and is thus attractive for its\ud simplicity. LMedS selects only a subset of the anchors with the\ud smallest residue for location calculation, but it tends to discard\ud more range measurements than necessary. Its performance can be\ud significantly improved, especially when the percentage of NLOS\ud links is not high. In this paper, we present an improved LMedS\ud method, which maximizes the subset of reliable anchors to be\ud used. We show via simulation that compared with the existing\ud LMedS method, the proposed algorithm has a significantly higher\ud localization accuracy and is more stable