Survey on Multi-Source Data Based Application and Exploitation Toward Smart Ship Navigation

Maritime ship transportation is not only the core infrastructure of the global logistics system but also is closely related to national security and sustainable development. However, the human factor remains the primary source of risk leading to maritime accidents during ship navigation. In recent years, multi-source data has been recognized as an important means to improve the efficiency of ship operations and navigation safety. In this paper, the major research methods and technical pathways of maritime multi-source data in recent years have been systematically reviewed, and a comprehensive technical framework from data acquisition and preprocessing to practical application has been constructed. Focusing on the data layer, application layer, and system layer, this paper comprehensively analyzes the key technologies of maritime navigation based on multi-source data. At the same time, this paper also highlights the advantages and cutting-edge methods of multi-source data in typical application scenarios—such as track extraction, target recognition, behavior detection, path planning, and collision avoidance—and analyzes their performance and adaptation strategies in different usage contexts. Through the combination of theory and engineering practice, this paper looks forward to the future development of ship intelligence and water transportation systems, providing a theoretical basis and technical support for the construction of intelligent shipping systems.