IEICE TRANSACTIONS on Fundamentals
Indoor Localization Algorithm for TDOA Measurement in NLOS Environments
Summary :
The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E97-A No.5 pp.1149-1152
- Publication Date
- 2014/05/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E97.A.1149
- Type of Manuscript
- LETTER
- Category
- Graphs and Networks
Authors
Xiaosheng YU
Northeastern University
Chengdong WU
Northeastern University
Long CHENG
Northeastern University
Keyword
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Xiaosheng YU, Chengdong WU, Long CHENG, "Indoor Localization Algorithm for TDOA Measurement in NLOS Environments" in IEICE TRANSACTIONS on Fundamentals,
vol. E97-A, no. 5, pp. 1149-1152, May 2014, doi: 10.1587/transfun.E97.A.1149.
Abstract: The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E97.A.1149/_p
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@ARTICLE{e97-a_5_1149,
author={Xiaosheng YU, Chengdong WU, Long CHENG, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Indoor Localization Algorithm for TDOA Measurement in NLOS Environments},
year={2014},
volume={E97-A},
number={5},
pages={1149-1152},
abstract={The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.},
keywords={},
doi={10.1587/transfun.E97.A.1149},
ISSN={1745-1337},
month={May},}
Copy
TY - JOUR
TI - Indoor Localization Algorithm for TDOA Measurement in NLOS Environments
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1149
EP - 1152
AU - Xiaosheng YU
AU - Chengdong WU
AU - Long CHENG
PY - 2014
DO - 10.1587/transfun.E97.A.1149
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E97-A
IS - 5
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - May 2014
AB - The complicated indoor environment such as obstacles causes the non-line of sight (NLOS) environment. In this paper, we propose a voting matrix based residual weighting (VM-Rwgh) algorithm to mitigate NLOS errors in indoor localization system. The voting matrix is employed to provide initial localization results. The residual weighting is used to improve the localization accuracy. The VM-Rwgh algorithm can overcome the effects of NLOS errors, even when more than half of the measurements contain NLOS errors. Simulation results show that the VM-Rwgh algorithm provides higher location accuracy with relatively lower computational complexity in comparison with other methods.
ER -
English
