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A Novel Specific Emitter Identification Algorithm Based on Amplitude Probability Distribution
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AI
DOI：10.1109/LCOMM.2022.3225284.png)
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Abstract
En 中文
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).
Keywords:
Feature extraction
Distortion
Nonlinear distortion
Probability distribution
Signal to noise ratio
Transforms
Training
amplitude probability distribution
specific emitter identification
subtle features
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