Jamming Pattern Open Set Recognition Based on Hyperspherical Triplet Coding

GAO Yulong; WANG Guoqiang; WANG Gang

doi:10.11999/JEIT230145

Volume 46 Issue 3

Mar. 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(3): 895-905

GAO Yulong, WANG Guoqiang, WANG Gang. Jamming Pattern Open Set Recognition Based on Hyperspherical Triplet Coding[J]. Journal of Electronics & Information Technology, 2024, 46(3): 895-905. doi: 10.11999/JEIT230145

Citation:

GAO Yulong, WANG Guoqiang, WANG Gang. Jamming Pattern Open Set Recognition Based on Hyperspherical Triplet Coding[J]. Journal of Electronics & Information Technology, 2024, 46(3): 895-905. doi: 10.11999/JEIT230145

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Jamming Pattern Open Set Recognition Based on Hyperspherical Triplet Coding

doi: 10.11999/JEIT230145 cstr: 32379.14.JEIT230145

School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China

Funds: The National Natural Science Foundation of China (62171163, 62271167)

Received Date: 2023-03-10
Rev Recd Date: 2023-11-05

Available Online: 2023-11-15

Publish Date: 2024-03-27

Abstract

Abstract

Jamming pattern recognition is an indispensable part of modern military communication countermeasure. With the emergence of various new malicious jamming patterns in complex electromagnetic environment, the judgment of unknown jamming has become more and more important. Therefore, the jamming pattern recognition algorithm is required to maintain the high-precision recognition of the known jamming, and can also complete the judgment of the unknown jamming to eliminate the influence of the unknown malicious jamming. Based on this, the jamming pattern recognition problem in the presence of unknown jamming as an open set recognition problem is modeled in this paper, and a jamming pattern open set recognition method based on hyperspherical triple coding is proposed. The proposed method uses hyperspherical triples to reduce the dimension of the input time-frequency image to improve the recognition accuracy, and then uses the meta-recognition classifier to accurately complete the open set recognition of the jamming pattern. The simulation results show that the algorithm can efficiently complete the jamming pattern recognition task in open space when the jamming-to-signal ratio is greater than –2 dB.
- Unknown interference signal,
- Open set recognition,
- Triplet loss,
- Hypersphere,
- Meta recognition

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References(23)

References

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