High Precision Navigation and Positioning for Multisource Sensors Based on Bibliometric and Contextual Analysis

With the increasing demand for high-precision positioning, integrated navigation technology has become a key approach to achieving accurate and reliable location tracking in modern intelligent mobile platforms. While previous studies have explored the application of various sensor combinations, there is still a lack of systematic analysis regarding the integration of the four major sensors: GNSS, INS, vision, and LiDAR. This study analyzes 5193 academic articles published between 2000 and 2024 in the Web of Science database, employing bibliometric analysis, network analysis, and content analysis to evaluate the development and application of these four sensors in integrated navigation systems. By reviewing the evolution of integrated navigation technology, the study examines four typical integration modes: GNSS/INS, INS/visual, GNSS/INS/visual, and GNSS/INS/visual/LiDAR, discussing their complementarity, fusion algorithm optimization, and emerging application scenarios. Despite significant progress in improving navigation accuracy and environmental adaptability, challenges persist in sensor cooperation and real-time processing capabilities in complex environments. The study concludes by summarizing existing research findings and identifying gaps, with future research focusing on optimizing multisensor fusion algorithms, enhancing system adaptability, improving error models, and enhancing sensor performance in adverse environmental conditions.