Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network

A specific emitter identification method based on deep residual network (DRN) is proposed to solve the problem that the traditional expert features relying on artificial extraction are difficult to characterize the subtle differences of specific emitters.The DRN is used to complete the identificatio...

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Autor principal:	Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao Xuanyu
Formato:	article
Lenguaje:	ZH
Publicado:	Editorial Office of Aero Weaponry 2021
Materias:	\|ads-b\|specific emitter identification\|deep residual network\|deep learning Motor vehicles. Aeronautics. Astronautics TL1-4050
Acceso en línea:	https://doaj.org/article/465c1e28afdc4ccd8eb15bf17b467144
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id	oai:doaj.org-article:465c1e28afdc4ccd8eb15bf17b467144
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spelling	oai:doaj.org-article:465c1e28afdc4ccd8eb15bf17b4671442021-11-30T00:13:33ZSpecific Emitter Identification of ADS-B Signal Based on Deep Residual Network1673-504810.12132/ISSN.1673-5048.2020.0095https://doaj.org/article/465c1e28afdc4ccd8eb15bf17b4671442021-08-01T00:00:00Zhttps://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/1631769555918-1785748409.pdfhttps://doaj.org/toc/1673-5048A specific emitter identification method based on deep residual network (DRN) is proposed to solve the problem that the traditional expert features relying on artificial extraction are difficult to characterize the subtle differences of specific emitters.The DRN is used to complete the identification task. The in-phase component (I-way) and the quadrature component (Q-way) of signal sample data are inputted into the DRN for training. The performance of the proposed method is evaluated by experiments on datasets containing actual collected ADS-B signals from different planes. The results show that the proposed DRN model achieves high classification accuracy without manual feature selection. Furthermore, data augmentation on signal-to-noise ratio can further improve the performance of the model.Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao XuanyuEditorial Office of Aero Weaponryarticle\|ads-b\|specific emitter identification\|deep residual network\|deep learningMotor vehicles. Aeronautics. AstronauticsTL1-4050ZHHangkong bingqi, Vol 28, Iss 4, Pp 24-29 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	\|ads-b\|specific emitter identification\|deep residual network\|deep learning Motor vehicles. Aeronautics. Astronautics TL1-4050
spellingShingle	\|ads-b\|specific emitter identification\|deep residual network\|deep learning Motor vehicles. Aeronautics. Astronautics TL1-4050 Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao Xuanyu Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
description	A specific emitter identification method based on deep residual network (DRN) is proposed to solve the problem that the traditional expert features relying on artificial extraction are difficult to characterize the subtle differences of specific emitters.The DRN is used to complete the identification task. The in-phase component (I-way) and the quadrature component (Q-way) of signal sample data are inputted into the DRN for training. The performance of the proposed method is evaluated by experiments on datasets containing actual collected ADS-B signals from different planes. The results show that the proposed DRN model achieves high classification accuracy without manual feature selection. Furthermore, data augmentation on signal-to-noise ratio can further improve the performance of the model.
format	article
author	Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao Xuanyu
author_facet	Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao Xuanyu
author_sort	Weng Lintianran, Peng Jinlin, He Yuan, Zhong Dudu, Peng Jianhua, Mao Xuanyu
title	Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
title_short	Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
title_full	Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
title_fullStr	Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
title_full_unstemmed	Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network
title_sort	specific emitter identification of ads-b signal based on deep residual network
publisher	Editorial Office of Aero Weaponry
publishDate	2021
url	https://doaj.org/article/465c1e28afdc4ccd8eb15bf17b467144
work_keys_str_mv	AT wenglintianranpengjinlinheyuanzhongdudupengjianhuamaoxuanyu specificemitteridentificationofadsbsignalbasedondeepresidualnetwork
_version_	1718406860292227072

Specific Emitter Identification of ADS-B Signal Based on Deep Residual Network

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