With the progress of science and technology and the steady improvement of the quality of production and life,the importance of unmanned aerial vehicle(UAV)in the industrial field is gradually revealed.At the same time,the number of illegal activities using UAV is also increasing year by year,and the detection and i-dentification of UAVs is imminent.The traditional detecting UAV algorithm is based on target matching,which needs to build a huge target library for complex matching calculation,and faces the defects of high target false alarm rate,high false negative rate and long recognition time.In recent years,deep learning technology makes breakthroughs in image processing,speech recognition,natural language processing and other fields.In this context,using the feature learning ability of deep learning technology can automatically learn target features to improve the accuracy of target recognition,which provide a new way for UAVs'detection and recognition.By collecting the latest research results in this field,the current recognition algorithms is summarized and expoun-ded from the technical point of view of radar,acoustic signal,visual signal and radio frequency,combined with intelligent technology.Finally,the main challenges facing the research in this field are summarized,and the fu-ture research priorities are prospected.
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