Underwater acoustic target recognition technology is an important part of underwater acoustic signal processing and an important technical support for underwater acoustic information acquisition and underwater acoustic information countermeasures. Aiming at the problems of large amount of detection data，low automation degree and low recognition efficiency in underwater acoustic target recognition，the application of deep learning in underwater acoustic target recognition was studied. First，the research status and the current challenges of underwater acoustic target recognition technology are introduced. Then，the network structure principle and improved form of deep learning are analyzed，and the application statuses of deep learning in underwater acoustic signal recognition and underwater acoustic image signal recognition are explained respectively. Finally，it is pointed out that due to the constraints of current technical conditions and the complex underwater environment，this method still has shortcomings. This mehod provides a reference for further optimization of deep learning algorithms，expansion of the scope of deep learning technology applications，and improvement of underwater acoustic target recognition efficiency.
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