Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (7): 226-235.doi: 10.11896/jsjkx.210600138

• Computer Network • Previous Articles     Next Articles

Survey of Deep Learning for Radar Emitter Identification Based on Small Sample

SU Dan-ning1, CAO Gui-tao1, WANG Yan-nan1, WANG Hong2, REN He2   

  1. 1 East China Normal University MoE Engineering Research Center of SW/HW Co-design Technology and Application,Shanghai 200062,China
    2 China Electronics Technology Group Corporation No.51 Research Institute,Shanghai 201802,China
  • Received:2021-06-17 Revised:2021-10-17 Online:2022-07-15 Published:2022-07-12
  • About author:SU Dan-ning,born in 1997,postgra-duate.Her main research interests include deep learning,radar emitter identification and so on.
    CAO Gui-tao,born in 1970,Ph.D,professor.Her main research interests include artificial intelligence,image analysis and understanding,medical big data processing.
  • Supported by:
    National Natural Science Foundation of China(61871186).

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Abstract: Traditional radar emitter identification methods can no longer meet the needs of identifying new-system radar emitters in the complicate and changeable electromagnetic environment.Deep learning methods can effectively extract the intra-pulse features of the unsorting radar emitter signal,quickly and accurately identify the radar intra-pulse modulation type,model type and emitter individual under complex environments such as low signal-to-noise ratio.However,in the reality,radar emitter signal is difficult to collect and cannot satisfy the training needs of traditional deep learning models.Therefore,the small sample radar emitter identification is one of hotspot and difficult questions of current research.Firstly,this paper reviews the research progress and application of various deep learning methods based on supervised learning for radar emitter recognition with small samples in recent years.Secondly,the research progress of radar emitter identification by small sample learning is introduced.Last,according to the current radar emitter identification research,the challenges and outlook for future research are put forward.

Key words: Deep learning, Intra-pulse feature, Radar emitter identification, Small sample

CLC Number: 

  • TP181
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