A Novel Specific Emitter Identification Algorithm Based on Amplitude Probability Distribution

被引:3
|
作者
Zhang, Chen [1 ]
Jiang, Hua [1 ]
Gong, Kexian [1 ]
Sun, Peng [1 ]
Wang, Wei [1 ]
机构
[1] Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
Feature extraction; Distortion; Nonlinear distortion; Probability distribution; Signal to noise ratio; Transforms; Training; amplitude probability distribution; specific emitter identification; subtle features;
D O I
10.1109/LCOMM.2022.3225284
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
We propose a novel specific emitter identification (SEI) algorithm based on amplitude probability distribution (APD). By studying the subtle differences in nonlinear distortion of power amplifiers, the proposed algorithm leverages the real signal amplitude interval probability distribution (AIPD) and analytical signal's constellation circle interval probability distribution (CIPD) to extract the local distortion features. The simulation results on both the simulated signal and actual signal show that compared to the benchmark methods, the proposed algorithm can achieve significant performance gains with relatively low complexity and has high robustness to training set size and prior information of signal to noise ratio (SNR).
引用
收藏
页码:671 / 675
页数:5
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