@inproceedings{0e714d63794b430aad9dc63f9e3d860f,
title = "A TOA-AOA Hybrid Localization Method in 5G Network with MIMO Antennas",
abstract = "The 5th generation wireless system (5G) is well known for its advantage in communication. Benefit from a set of new features, it also has the potential capability of high accurate localization and helping Global Navigation Satellite System (GNSS) relieve the problem of lacking visible satellites in urban environment. However, the network time synchronization error among different 5G base stations (BSs) has become a main challenge to improve positioning accuracy of 5G network. Currently, the time synchronization accuracy is about 50-ns level which results in a range error of 15 m level when time of arrival (TOA) is used for positioning. This work proposes a new TOA-AOA hybrid positioning scheme employing Multi-Input Multi-Output (MIMO) antennas which can provide a high degree of angular resolvability. Taylor series least square method, originally designed for TOA measurements, has been extended to the TOA-AOA hybrid positioning scheme. The synchronization error of each BS is modelled as an unknown quantity to be solved rather than a Gaussian noise with zero mean and a certain variance, which makes it possible to estimate the synchronization error of each BS precisely and finally get rid of the effect of it. Different scenarios for network synchronization are investigated in this paper. Simulation results show that the proposed method can significantly improve the accuracy of the 5G-based positioning and outperforms conventional algorithms without considering the network synchronization error.",
keywords = "5G, Synchronization error, TOA/AOA, Taylor series least square",
author = "Lu Bai and Chao Sun and Hongbo Zhao and Cheong, \{Joon Wayn\} and Dempster, \{Andrew G.\} and Wenquan Feng",
note = "Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 12th China Satellite Navigation Conference, CSNC 2021 ; Conference date: 22-05-2021 Through 25-05-2021",
year = "2021",
doi = "10.1007/978-981-16-3138-2\_28",
language = "英语",
isbn = "9789811631375",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "285--295",
editor = "Changfeng Yang and Jun Xie",
booktitle = "China Satellite Navigation Conference, CSNC 2021, Proceedings",
address = "德国",
}