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

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.