A Review of Communication Specific Emitter Identification Based on Deep Learning
Under non-cooperative conditions,signal detection,automatic modulation mode identification and Specific Emitter Identification(SEI)are crucial in battlefield communication reconnaissance.With the rapid development of wireless communication technology,the types of radiation sources have become increasingly diverse,the signal system has become more complex,and the harsh electromagnetic environment has brought significant challenges to SEI.In recent years,with the rapid advancement of deep learning and its practical applications in fields such as natural language processing and computer vision,it has gradually been applied in SEI tasks and has achieved rich research results.Given the lack of open-source datasets in the existing literature,available open-source datasets are compiled and a detailed review of SEI methods is conducted from two dimensions:knowledge-driven and data-driven approaches,including expert system methodologies and deep learning technologies.The comparative analysis reveals the advantages of deep learning in SEI tasks.Finally,the development directions of SEI are summarized,concerning the existing problems faced by deep learning in the field of SEI.
communication radiation sourceSEIdeep learningdata-drivenopen-set identification
国家科技期刊平台
NSTL
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