Low SNR Multi-Emitter Signal Sorting and Recognition Method Based on Low-Order Cyclic Statistics CWD Time-Frequency Images and the YOLOv5 Deep Learning Model

It is difficult for traditional signal-recognition methods to effectively classify and identify multiple emitter signals in a low SNR environment. This paper proposes a multi-emitter signal-feature-sorting and recognition method based on low-order cyclic statistics CWD time-frequency images and the...

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Detalles Bibliográficos
Autores principales: Huang, Dingkun, Yan, Xiaopeng, Hao, Xinhong, Dai, Jian, Wang, Xinwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609638/
https://www.ncbi.nlm.nih.gov/pubmed/36298133
http://dx.doi.org/10.3390/s22207783

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9609638/
https://www.ncbi.nlm.nih.gov/pubmed/36298133
http://dx.doi.org/10.3390/s22207783

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