TY - GEN
T1 - Specific Emitter Identification Using Regression Analysis between Individual Features and Physical Parameters
AU - Zhao, Yaqin
AU - Yang, Rongqian
AU - Wu, Longwen
AU - He, Shengyang
AU - Niu, Jinpeng
AU - Zhao, Liang
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In this paper, a semi-physical simulation platform and ADS are used to acquire the signals of three types of specific emitters, then high-order spectral analysis and variational modal decomposition are used to extract features of the signals. The phase noise of the oscillator and the bias voltage of the power amplifier are used as independent variables to study their influence on the features, based on which the correlation analysis is carried out. Regression fitting is performed on the variables with significant correlation to obtain a regression function, then a feature-weighted support vector machine is constructed for classification. The results show that the accuracy of the proposed identification algorithm using regression analysis is more than 10 percent higher than that of the single-kernel support vector machine under the same signal-To-noise ratio.
AB - In this paper, a semi-physical simulation platform and ADS are used to acquire the signals of three types of specific emitters, then high-order spectral analysis and variational modal decomposition are used to extract features of the signals. The phase noise of the oscillator and the bias voltage of the power amplifier are used as independent variables to study their influence on the features, based on which the correlation analysis is carried out. Regression fitting is performed on the variables with significant correlation to obtain a regression function, then a feature-weighted support vector machine is constructed for classification. The results show that the accuracy of the proposed identification algorithm using regression analysis is more than 10 percent higher than that of the single-kernel support vector machine under the same signal-To-noise ratio.
KW - feature extraction
KW - regression analysis
KW - specific emitter identification
KW - weighted support vector machine
UR - https://www.scopus.com/pages/publications/85149106700
U2 - 10.1109/ICISPC57208.2022.00017
DO - 10.1109/ICISPC57208.2022.00017
M3 - 会议稿件
AN - SCOPUS:85149106700
T3 - Proceedings - 2022 6th International Conference on Imaging, Signal Processing and Communications, ICISPC 2022
SP - 48
EP - 52
BT - Proceedings - 2022 6th International Conference on Imaging, Signal Processing and Communications, ICISPC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Imaging, Signal Processing and Communications, ICISPC 2022
Y2 - 22 July 2022 through 24 July 2022
ER -