The effective identification and monitoring of ship targets is essential for safeguarding the maritime rights and ensuring the navigation safety. In line with the acquisition form of the ship target information, this paper reviews the ship target recognition technology based on several main information acquisition sources of the ship targets, including the radiated noise signal, the radar echo signal, the satellite remote sensing image, the synthetic aperture radar image, the infrared image and the visible image. The current research difficulties in the ship target recognition methods based on different signal sources are analyzed, involving the high mission correlation, the high calculation cost and the long running time. Combined with the development of the deep learning technology in the speech recognition, the image recognition and other fields, the typical target recognition methods based on the deep learning technology, the Faster R-CNN and the YOLO, are applied in the ship target recognition. It is proposed that the introduction of the deep learning technology into the ship target recognition field indicates a new direction for the research of the ship target recognition methods with better robustness, higher accuracy and better real-time performance.

ships  /  target recognition  /  deep learning