As technology develops,the modulation type of underwater acoustic communication signals has gradually evolves from typical traditional modulation methods,to many new modulation methods developed by underwater acoustic communication machine manufacturers privately,which restricts the practicality of the existing closed-set modulation and identification technology of underwater acoustic communication signals.To address the problem that there are few open-set recognition methods based on deep learning for underwater acoustic communication signals,an open-set recognition method based on the YOLO network and OpenMax model was proposed.Using the output characteristics of the YO-LOv5 network,the traditional process of the OpenMax model was improved,and a two-step testing pro-cess was proposed to realize the open-set recognition of underwater acoustic communication signals un-der multipath channels.Simulation experiments show that when the normalization coefficient is 0.5 and the signal-to-noise ratio is 10 dB,the normalized accuracy reaches more than 90%.The measured data also verify the effectiveness of the proposed method.
underwater acoustic communicationmodulation recognitionopen-set recognitiontwo-step testing process
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