Specific Emitter Identification

Specific emitter identification (SEI) aims to uniquely identify wireless transmitters based on subtle variations in their emitted signals, often leveraging machine learning to analyze complex radio frequency (RF) characteristics. Current research heavily utilizes deep learning models, particularly convolutional neural networks (CNNs) and transformers, to classify transmitters with high accuracy, even under challenging conditions like low signal-to-noise ratios and interference. This field is crucial for improving wireless security, spectrum management, and enabling advanced applications such as physical layer authentication and dynamic spectrum access, with ongoing efforts focused on improving model efficiency and adaptability to diverse and dynamic environments.