Emitter Individual Identification Based on Nonlinearity Analysis of Oscillators

Abstract

Background: According to the characteristics of phase noise, phase noise power spectrum feature was used for emitter individual identification. Methods: For different emitter individuals, we established a phase noise model with the influence of both transmitter and receiver based on the research of its characteristics. Using power spectrum of phase noise, the corresponding scattered information entropy was proposed. The same type of communication equipments can be identified by Minimum Error Minimax Probability Machine (MEMPM) classifier through extracting this feature at a different frequency offset. Results: Simulation results show that the new features can be effectively used to classify emitter individuals with stable classification performance. Conclusion: According to the simulation, when the SNR was higher than 10dB, the accuracy rate was higher than 90%. It proved that the method is useful and effective. In addition, the recognition performance of the proposed method is very stable, showing the stability of the device phase noise. Therefore, it can be used in practice.