- Tytuł:
- Specific emitter identification using geometric features of frequency drift curve
- Autorzy:
-
Zhao, Y.
Wui, L.
Zhang, J.
Li, Y. - Powiązania:
- https://bibliotekanauki.pl/articles/200575.pdf
- Data publikacji:
- 2018
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
specific emitter identification
geometric features
frequency drift
adaptive fractional spectrogram
support vector machine
emiter
cechy geometryczne
dryf częstotliwości
spektrogram - Opis:
- Specific emitter identification (SEI) is a technique for recognizing different emitters of the same type which have the same modulation parameters. Using only the classic modulation parameters for recognition, one cannot distinguish different emitters of a same type. To solve the problem, new features urgently need to be developed for recognition. This paper focuses on the common phenomenon of frequency drift, defines geometric features of frequency drift curve and, finally, proposes a practical algorithm of specific emitter identification using the geometric features. The proposed algorithm consists of three processes: instantaneous frequency estimation based on the adaptive fractional spectrogram, feature extraction of frequency drift curve based on geometric methods for describing a curve and recognition process based on support vector machine. Simulation results show that the identification rate is generally more than 98% above –5 dB of signal to noise ratio (SNR), and real data experiment verifies the practical performance of the proposed algorithm.
- Źródło:
-
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2018, 66, 1; 99-108
0239-7528 - Pojawia się w:
- Bulletin of the Polish Academy of Sciences. Technical Sciences
- Dostawca treści:
- Biblioteka Nauki
Artykuł