Assist. Prof. Dr. Xiao Yin | Satellite Navigation | Academic Excellence Award

Xiao Yin is a researcher and lecturer specializing in satellite navigation, integrated positioning systems, and intelligent sensing technologies. He currently serves as a Lecturer at Zhejiang A&F University, Hangzhou, China, where his academic work focuses on advanced Global Navigation Satellite System (GNSS) theories, GNSS/INS integration, and emerging deep learning–based visual positioning and mapping techniques. He also completed postdoctoral research at Southeast University, Nanjing, further strengthening his expertise in real-time high-precision navigation. Xiao Yin earned his PhD in Engineering from Information Engineering University, Zhengzhou, with a dissertation centered on the theory and application of real-time multi-GNSS PPP-RTK and inertial navigation system (INS) integration. His earlier academic training includes a Master of Engineering from Tongji University, where he investigated GPS/BDS real-time navigation models, and a Bachelor of Engineering from Shenyang Jianzhu University. This strong academic foundation has enabled him to bridge theoretical navigation models with real-world engineering applications. His research contributions span precise point positioning (PPP), PPP-RTK, multi-GNSS performance analysis, atmospheric delay modeling, and robust filtering methods such as Kalman, Unscented Kalman, and adaptive nonlinear filtering. In recent years, his work has expanded into interdisciplinary applications, including LiDAR-based canopy estimation, subway excavation settlement prediction, offshore and underwater navigation, and intelligent deformation monitoring using deep learning models like BiLSTM and ensemble methods. Xiao Yin has published extensively in high-impact international journals such as Marine Geodesy, Measurement, Remote Sensing, IEEE Sensors Journal, and Engineering Research Express. His research is recognized for improving positioning accuracy and reliability in challenging environments such as dense urban areas, offshore regions, forests, and underground infrastructure, contributing significantly to the advancement of modern navigation and geospatial engineering.

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