An Indoor Localization Algorithm Based on Convex Optimization under NLOS Environment

DOI

10.2991/jimec-18.2018.39How to use a DOI?

Keywords

NLOS; localization; robust; QCQP

Abstract

In the actual indoor localization system, the existence of non-line-of-sight (NLOS) errors is a very important reason for the reduction of localization accuracy Therefore, how to deal with NLOS error becomes a research hotspot in the study of localization technology. In this paper, a robust quadratically constrained quadratic programming (QCQP) method is proposed for NLOS error. The algorithm does not need to know the distribution information of NLOS errors, nor does it need to judge the NLOS status of each path, and the complexity is low, which has high practical application value.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Long Zhang
AU  - Pinpin Lv
AU  - Chunqi Jiang
PY  - 2018/12
DA  - 2018/12
TI  - An Indoor Localization Algorithm Based on Convex Optimization under NLOS Environment
BT  - Proceedings of the 2018 3rd Joint International Information Technology，Mechanical and Electronic Engineering Conference (JIMEC 2018)
PB  - Atlantis Press
SP  - 183
EP  - 186
SN  - 2589-4943
UR  - https://doi.org/10.2991/jimec-18.2018.39
DO  - 10.2991/jimec-18.2018.39
ID  - Zhang2018/12
ER  -