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Volume 44 Issue 6
Jun.  2022
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SHI Ya, ZHANG Wenbo, ZHU Mingzhe, WANG Lei, XU Shengjun. Specific Radar Emitter Identification: A Comprehensive Review[J]. Journal of Electronics & Information Technology, 2022, 44(6): 2216-2229. doi: 10.11999/JEIT210161
Citation: SHI Ya, ZHANG Wenbo, ZHU Mingzhe, WANG Lei, XU Shengjun. Specific Radar Emitter Identification: A Comprehensive Review[J]. Journal of Electronics & Information Technology, 2022, 44(6): 2216-2229. doi: 10.11999/JEIT210161

Specific Radar Emitter Identification: A Comprehensive Review

doi: 10.11999/JEIT210161
Funds:  The National Natural Science Foundation of China (61803293, 61501357, 61301286, 61203137), The Natural Science Basic Research Plan in Shaanxi Province of China (2019JQ760)
  • Received Date: 2021-02-25
  • Rev Recd Date: 2022-04-21
  • Available Online: 2022-04-26
  • Publish Date: 2022-06-21
  • Specific radar emitter identification distinguishes each radar emitter based on the extracted individual features, which is crucial for electronic countermeasures. With the rapid development of deep learning, specific radar emitter identification using deep learning architecture draws great attention recently. Despite many years of research and rich achievements, there is still lack of a comprehensive review about specific radar emitter identification at present. Therefore, a systematic review is provided in this paper from four aspects: (1) the mechanism analysis of identification; (2) the handcrafted feature-based identification methods; (3) the deep learning-based identification methods; (4) and the testing datasets. Finally, the current status and the future directions are summarized, aiming at promoting the new development of specific radar emitter identification.
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