Abstract: With the in-depth development of maritime digitalization and the comprehensive application of the S-100 universal hydrographic data model, traditional electronic navigational charts are undergoing a paradigm evolution towards Smart Charts. Based on the S-100 unified data model and integrating shipborne and shore-based multi-source dynamic information, Smart Charts serve as a comprehensive navigation intelligent platform that provides spatial analysis, situational awareness and auxiliary decision support for intelligent navigation. Based on systematically sorting out the technical system and research progress of Smart Charts, this paper summarizes the research from four dimensions: spatial analysis foundation, data model system, visualization expression and application services. In terms of spatial analysis, it analyzes the enlightenment of geographic information technology evolution on chart reconstruction, and discusses the construction of continuous water depth field and spatial interpolation methods; in terms of data model, it explains the architectural characteristics of static basic data, dynamic environmental data and information interoperability model under the S-100 framework; in terms of visualization expression, it analyzes the expression methods in multi-source data integration from two dimensions of production-oriented cartographic visualization and application-oriented spatiotemporal visualization; in terms of application services, it expounds typical application scenarios from four aspects: multi-source data fusion, complex environmental situational awareness, intelligent route planning and risk early warning decision-making. The research shows that Smart Charts are evolving from basic display tools to comprehensive navigation intelligent platforms, which can provide key technical support for intelligent ships and smart shipping; although its core technical system has been initially formed, it still faces challenges in standardized production, real-time fusion computing, 3D visualization evaluation, human-machine collaborative decision-making and other aspects. This study can provide a reference for the subsequent research in the field of intelligent navigation and Smart Charts.