Accurate identification on individual similar communication emitters by using HVG-NTE feature

• Autorzy: Li Ke , Ge Wei , Yang Xiaoya , Xu Zhengrong

Identyfikatory

DOI

10.24425/bpasts.2021.136741

• Języki publikacji: EN

Abstrakty

EN

Individual identification of similar communication emitters in the complex electromagnetic environment has great research value and significance in both military and civilian fields. In this paper, a feature extraction method called HVG-NTE is proposed based on the idea of system nonlinearity. The shape of the degree distribution, based on the extraction of HVG degree distribution, is quantified with NTE to improve the anti-noise performance. Then XGBoost is used to build a classifier for communication emitter identification. Our method achieves better recognition performance than the state-of-the-art technology of the transient signal data set of radio stations with the same plant, batch, and model, and is suitable for a small sample size.

Słowa kluczowe

EN

communication emitter; identification; feature extraction; HVG; NTE

PL

emiter komunikacji; identyfikacja; wyodrębnianie cech; HVG; NTE

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2021
• Tom: Vol. 69, nr 2
• Strony: art. no. e136741
• Opis fizyczny: Bibliogr. 33 poz., rys.

Twórcy

autor

Li Ke

• School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, 230036, China
• Anhui Provincial Engineering Laboratory for Beidou Precision Agriculture Information, Anhui Agricultural University, Hefei, Anhui, 230036, China
• Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University, Shanghai, 200072, China

• https://orcid.org/0000-0001-7279-5015

autor

Ge Wei

• School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, 230036, China
• Anhui Provincial Engineering Laboratory for Beidou Precision Agriculture Information, Anhui Agricultural University, Hefei, Anhui, 230036, China

• https://orcid.org/0000-0003-0475-3117

autor

Yang Xiaoya

• School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, 230036, China
• Anhui Provincial Engineering Laboratory for Beidou Precision Agriculture Information, Anhui Agricultural University, Hefei, Anhui, 230036, China

autor

Xu Zhengrong

• School of Information and Computer, Anhui Agricultural University, Hefei, Anhui, 230036, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).