Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

A Closed form Localization Method using AOA and TOA Measurements based on WSN in NLOS Environments

Authors
Ruirui LIU, Jiexin YIN, Ding WANG
Corresponding Author
Ruirui LIU
Available Online July 2017.
DOI
10.2991/eia-17.2017.26How to use a DOI?
Keywords
AOA; CRLB; NLOS; WLS; WSN; TOA
Abstract

This paper proposed a closed form localization method based on wireless sensor network (WSN) in the non-line of sight (NLOS) environment. We utilized the angle of arrival (AOA) and time of arrival (TOA) measurements to determine the positions of target and reflectors according to the localization geometry. A two-step weighted least square (WLS) estimator is exhibited, where the first-order error analysis is used. In addition, a derivation of the Cram,r-Rao lower bound (CRLB) is presented and the performance will be verified by the simulations.

Copyright
© 2017, 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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Volume Title
Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.26
ISSN
1951-6851
DOI
10.2991/eia-17.2017.26How to use a DOI?
Copyright
© 2017, 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/).

Cite this article

TY  - CONF
AU  - Ruirui LIU
AU  - Jiexin YIN
AU  - Ding WANG
PY  - 2017/07
DA  - 2017/07
TI  - A Closed form Localization Method using AOA and TOA Measurements based on WSN in NLOS Environments
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 121
EP  - 125
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.26
DO  - 10.2991/eia-17.2017.26
ID  - LIU2017/07
ER  -