Specific Emitter Identification Based on IQ Imbalance and PA Nonlinearity Joint Estimation

Specific emitter identification (SEI) plays an important role in both civil and military communication fields, offering the means to distinguish individual radio emitters. The intrinsic hardware distortions incurred by manufacturing imperfection can be used to identify emitters as radio frequency fingerprints (RFFs). However, RFFs extraction is highly challenging due to the coupling effects of the transmitter’s components, especially for the mixer and power amplifier (PA). This paper proposes a novel SEI scheme targeting in-phase/quadrature (IQ) imbalance and PA nonlinearity for quadrature amplitude modulation (QAM) systems. Our algorithm decouples IQ imbalance and PA non-linearity by leveraging the amplitude distribution characteristics of the QAM system before we estimate each of them, and then classify individual emitters by training a traditional classifier. Simulation results indicate that when handling 72 emitters characterized by randomly distributed IQ imbalances and PA nonlinearities, the proposed scheme can achieve a classification accuracy rate exceeding 90%.