A Multipulse Radar Signal Recognition Approach via HRF-Net Deep Learning Models

In the field of electronic countermeasure, the recognition of radar signals is extremely important. This paper uses GNU Radio and Universal Software Radio Peripherals to generate 10 classes of close-to-real multipulse radar signals, namely, Barker, Chaotic, EQFM, Frank, FSK, LFM, LOFM, OFDM, P1, and...

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Detalles Bibliográficos
Autores principales: Li, Ji, Zhang, Huiqiang, Ou, Jianping, Wang, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192198/
https://www.ncbi.nlm.nih.gov/pubmed/34188675
http://dx.doi.org/10.1155/2021/9955130

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8192198/
https://www.ncbi.nlm.nih.gov/pubmed/34188675
http://dx.doi.org/10.1155/2021/9955130

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