Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things
Unmanned aerial vehicles (UAVs) have broad application potential for the Internet of Things (IoT) due to their small size, low cost, and flexible control. At present, the main positioning method for UAVs is the use of GPS. However, GPS positioning may be affected by stronger electromagnetic signals...
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Series: | Wireless Communications and Mobile Computing |
Online Access: | http://dx.doi.org/10.1155/2019/2850263 |
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doaj-efa38d33f45844d89a1dc01b05d27ff52020-11-25T00:44:42ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772019-01-01201910.1155/2019/28502632850263Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of ThingsJingcheng Zhao0Xinru Fu1Zongkai Yang2Fengtong Xu3School of Electronics and Information Engineering, Beihang University, ChinaSchool of Electronics and Information Engineering, Beihang University, ChinaSchool of Electronics and Information Engineering, Beihang University, ChinaSchool of Electronics and Information Engineering, Beihang University, ChinaUnmanned aerial vehicles (UAVs) have broad application potential for the Internet of Things (IoT) due to their small size, low cost, and flexible control. At present, the main positioning method for UAVs is the use of GPS. However, GPS positioning may be affected by stronger electromagnetic signals from spoofing attacks. In this study, a radar-assisted positioning method based on 5G millimeter waves is proposed. In 5G end-to-end network slices, the rotors of UAVs can be detected and identified by deploying 5G millimeter wave radar. High-resolution range profile (HRRP) is used to obtain the UAV location in the detection zone. Micro-Doppler characteristics are used to identify the UAVs and the cepstrum method is used to extract the number and speed information of the UAV rotor. The sinusoidal frequency modulation (SFM) parameter optimization method is used to separate multiple UAVs. The proposed method provides information on the number of UAVs, the position of the UAV, the number of rotors, and the rotation speed of each rotor. The simulation results show that the proposed radar detection method is well suited for UAV detection and identification and provides a valid GPS-independent method for UAV tracking.http://dx.doi.org/10.1155/2019/2850263 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jingcheng Zhao Xinru Fu Zongkai Yang Fengtong Xu |
spellingShingle |
Jingcheng Zhao Xinru Fu Zongkai Yang Fengtong Xu Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things Wireless Communications and Mobile Computing |
author_facet |
Jingcheng Zhao Xinru Fu Zongkai Yang Fengtong Xu |
author_sort |
Jingcheng Zhao |
title |
Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things |
title_short |
Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things |
title_full |
Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things |
title_fullStr |
Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things |
title_full_unstemmed |
Radar-Assisted UAV Detection and Identification Based on 5G in the Internet of Things |
title_sort |
radar-assisted uav detection and identification based on 5g in the internet of things |
publisher |
Hindawi-Wiley |
series |
Wireless Communications and Mobile Computing |
issn |
1530-8669 1530-8677 |
publishDate |
2019-01-01 |
description |
Unmanned aerial vehicles (UAVs) have broad application potential for the Internet of Things (IoT) due to their small size, low cost, and flexible control. At present, the main positioning method for UAVs is the use of GPS. However, GPS positioning may be affected by stronger electromagnetic signals from spoofing attacks. In this study, a radar-assisted positioning method based on 5G millimeter waves is proposed. In 5G end-to-end network slices, the rotors of UAVs can be detected and identified by deploying 5G millimeter wave radar. High-resolution range profile (HRRP) is used to obtain the UAV location in the detection zone. Micro-Doppler characteristics are used to identify the UAVs and the cepstrum method is used to extract the number and speed information of the UAV rotor. The sinusoidal frequency modulation (SFM) parameter optimization method is used to separate multiple UAVs. The proposed method provides information on the number of UAVs, the position of the UAV, the number of rotors, and the rotation speed of each rotor. The simulation results show that the proposed radar detection method is well suited for UAV detection and identification and provides a valid GPS-independent method for UAV tracking. |
url |
http://dx.doi.org/10.1155/2019/2850263 |
work_keys_str_mv |
AT jingchengzhao radarassisteduavdetectionandidentificationbasedon5gintheinternetofthings AT xinrufu radarassisteduavdetectionandidentificationbasedon5gintheinternetofthings AT zongkaiyang radarassisteduavdetectionandidentificationbasedon5gintheinternetofthings AT fengtongxu radarassisteduavdetectionandidentificationbasedon5gintheinternetofthings |
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1725273944859082752 |