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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Main Authors: Jingcheng Zhao, Xinru Fu, Zongkai Yang, Fengtong Xu
Format: Article
Language:English
Published: Hindawi-Wiley 2019-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2019/2850263
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spelling 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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