Specific Emitter Identification Based on Variational Mode Decomposition and Spectral Features in Single Hop and Relaying Scenarios

Specific emitter identification is the process of identifying or discriminating different emitters based on the radio frequency fingerprints extracted from the received signal. Due to inherent non-linearities of the power amplifiers of emitters, these fingerprints provide distinguish features for emitter identification. In this paper, we develop an emitter identification based on variational mode decomposition and spectral features (VMD-SF). As VMD decomposes the received signal simultaneously into various temporal and spectral modes, we choose to explore different spectral features, including spectral flatness, spectral brightness, and spectral roll-off for improving the identification accuracy contrary to existing temporal features-based methods. For demonstrating the robustness of VMD in decomposing the received signal into emitter-specific modes, we also develop a VMD-entropy and moments (<inline-formula> <tex-math notation="LaTeX">$EM^{2}$ </tex-math></inline-formula>) method based on existing temporal features extracted from the Hilbert Huang transform of the emitter-specific temporal modes. Our proposed method has three major steps: received signal decomposition using VMD, feature extraction, and emitter identification. We evaluate the performance of the proposed methods using the probability of correct classification (<inline-formula> <tex-math notation="LaTeX">$P_{cc}$ </tex-math></inline-formula>) both in single hop and in relaying scenario by varying the number of emitters. To demonstrate the superior performance of our proposed methods, we compared our methods with the existing empirical mode decomposition-(entropy-, first-, and second-order moments) (EMD-<inline-formula> <tex-math notation="LaTeX">$EM^{2}$ </tex-math></inline-formula>) method both in terms of <inline-formula> <tex-math notation="LaTeX">$P_{cc}$ </tex-math></inline-formula> and computational complexity. Results depict that the proposed VMD-SF emitter identification method outperforms the proposed VMD-<inline-formula> <tex-math notation="LaTeX">$EM^{2}$ </tex-math></inline-formula> method and the existing EMD-<inline-formula> <tex-math notation="LaTeX">$EM^{2}$ </tex-math></inline-formula> method both in single hop and relaying scenarios for a varying number of emitters. In addition, the proposed VMD-SF method has lowest computational cost as compared with the aforementioned methods.