Autonomous navigation is a key technology for deep space exploration, and several autonomous landing missions on extraterrestrial planets have been executed by China and other nations. Autonomous visual navigation technology based on craters is a current research hotspot. Numerous planets have rich crater features, and pose estimation based on terrain features is an important technology for visual navigation. This work first briefly introduces the recent application progress of navigation technology in the field of deep space exploration and the classification of autonomous navigation methods. Visual navigation has been classified according to sensor imaging, focusing on the terrain relative navigation method based on craters. Subsequently, the advantages and difficulties of the crater-based method are summarized, definition and data types of craters are introduced, and domestic and foreign research institutions and personnel have been presented. Moreover, the navigation method based on craters is divided into three stages, crater detection, crater recognition, and pose calculation, and the research advances in crater detection methods, from supervised detection, to unsupervised detection, and finally to composite detection, are introduced thoroughly. The work introduces domestic and foreign methods of crater recognition according to the stage and the presence or absence of initial attitude information, respectively, and then introduces the pose calculation method based on image information and the method combined with dynamic models, respectively. Finally, crater-based visual navigation technology is summarized, and prospects for its development are discussed.