Using ship radiated noise for target identification and classification is an important research topic in the field of underwater acoustics. This article provides a comprehensive overview of data acquisition methods and feature extraction techniques for ship radiated noise,as well as target recognition methods. Firstly,the article introduces four databases with abundant data types of radiated noise. Secondly,it presents feature extraction techniques for radiated noise,including line spectrum recognition,wavelet analysis,and sub-linear features. Finally, the article discusses target recognition and classification techniques in the field of radiated noise,covering traditional methods such as support vector machines and deep learning approaches. This article systematically summarizes classification techniques based on ship radiated noise,offering valuable insights for research on ship target classification and identification.