Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array

Safety, security, and privacy are three critical concerns affiliated with the use of drones in everyday life. Considering their ever-shrinking sizes and capabilities, being aware of drone activities in the vicinity becomes an important surveillance item. Therefore, keeping track of drones and prefer...

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Autores principales:	Batuhan Kaplan, Ibrahim Kahraman, Ali Riza Ekti, Serhan Yarkan, Ali Gorcin, Mehmet Kemal Ozdemir, Hakan Ali Cirpan
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	STFT cyclostationarity direction finding FHSS MUSIC drone remote controller Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/1079af0cacfb478eb5e94a2789d03a78
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spelling	oai:doaj.org-article:1079af0cacfb478eb5e94a2789d03a782021-11-18T00:00:53ZDetection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array2169-353610.1109/ACCESS.2021.3127199https://doaj.org/article/1079af0cacfb478eb5e94a2789d03a782021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9611266/https://doaj.org/toc/2169-3536Safety, security, and privacy are three critical concerns affiliated with the use of drones in everyday life. Considering their ever-shrinking sizes and capabilities, being aware of drone activities in the vicinity becomes an important surveillance item. Therefore, keeping track of drones and preferably their controllers should be included into the already-existing security measures. In this study, a frequency hopping spread spectrum (FHSS) type drone controller signal detection and emitter direction finding framework is proposed to achieve aforementioned goals. Since drone communications signals generally coexist with other FHSS signals in 2.4 GHz industrial, scientific, and medical (ISM) band, first, a method based on cyclostationarity analysis is proposed to distinguish the drone radio controller signals from other signals utilizing 2.4 GHz ISM band. Then, a variant of short-term Fourier transform is introduced to extract the parameters of detected drone remote controller signals. The correct hopping signals are then aggregated based on the clustered parameters to obtain their combined baseband equivalent signal. Furthermore, the resampling process is applied to reduce the unrelated samples in the spectrum and represent the spectrum with the reconstructed signal, which has a much lower bandwidth than the spread bandwidth. Finally, two different multiple signal classification algorithms are utilized to estimate the direction of the drone controller relative to the receiving system. In order to validate the overall performance of the proposed method, the introduced framework is implemented on hardware platforms and tested under real-world conditions. A uniform linear antenna array is utilized to capture over-the-air signals in hilly terrain suburban environments by considering both line-of-sight and non-line–of-sight cases. Direction estimation performance is presented in a comparative manner and relevant discussions are provided.Batuhan KaplanIbrahim KahramanAli Riza EktiSerhan YarkanAli GorcinMehmet Kemal OzdemirHakan Ali CirpanIEEEarticleSTFTcyclostationaritydirection findingFHSSMUSICdrone remote controllerElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 152057-152069 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	STFT cyclostationarity direction finding FHSS MUSIC drone remote controller Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	STFT cyclostationarity direction finding FHSS MUSIC drone remote controller Electrical engineering. Electronics. Nuclear engineering TK1-9971 Batuhan Kaplan Ibrahim Kahraman Ali Riza Ekti Serhan Yarkan Ali Gorcin Mehmet Kemal Ozdemir Hakan Ali Cirpan Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
description	Safety, security, and privacy are three critical concerns affiliated with the use of drones in everyday life. Considering their ever-shrinking sizes and capabilities, being aware of drone activities in the vicinity becomes an important surveillance item. Therefore, keeping track of drones and preferably their controllers should be included into the already-existing security measures. In this study, a frequency hopping spread spectrum (FHSS) type drone controller signal detection and emitter direction finding framework is proposed to achieve aforementioned goals. Since drone communications signals generally coexist with other FHSS signals in 2.4 GHz industrial, scientific, and medical (ISM) band, first, a method based on cyclostationarity analysis is proposed to distinguish the drone radio controller signals from other signals utilizing 2.4 GHz ISM band. Then, a variant of short-term Fourier transform is introduced to extract the parameters of detected drone remote controller signals. The correct hopping signals are then aggregated based on the clustered parameters to obtain their combined baseband equivalent signal. Furthermore, the resampling process is applied to reduce the unrelated samples in the spectrum and represent the spectrum with the reconstructed signal, which has a much lower bandwidth than the spread bandwidth. Finally, two different multiple signal classification algorithms are utilized to estimate the direction of the drone controller relative to the receiving system. In order to validate the overall performance of the proposed method, the introduced framework is implemented on hardware platforms and tested under real-world conditions. A uniform linear antenna array is utilized to capture over-the-air signals in hilly terrain suburban environments by considering both line-of-sight and non-line–of-sight cases. Direction estimation performance is presented in a comparative manner and relevant discussions are provided.
format	article
author	Batuhan Kaplan Ibrahim Kahraman Ali Riza Ekti Serhan Yarkan Ali Gorcin Mehmet Kemal Ozdemir Hakan Ali Cirpan
author_facet	Batuhan Kaplan Ibrahim Kahraman Ali Riza Ekti Serhan Yarkan Ali Gorcin Mehmet Kemal Ozdemir Hakan Ali Cirpan
author_sort	Batuhan Kaplan
title	Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
title_short	Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
title_full	Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
title_fullStr	Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
title_full_unstemmed	Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array
title_sort	detection, identification, and direction of arrival estimation of drone fhss signals with uniform linear antenna array
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/1079af0cacfb478eb5e94a2789d03a78
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Detection, Identification, and Direction of Arrival Estimation of Drone FHSS Signals With Uniform Linear Antenna Array

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