- ISSN 0258-2724
- CN 51-1277/U
- EI Compendex
- Scopus
- Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
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| Citation: | WANG Bailiang, MA Zheng, LIU Lin, LIANG Xianming, LIU Gang. Resilient Positioning Navigation and Timing System and Key Technologies for Rail Transit[J]. Journal of Southwest Jiaotong University. doi: 10.3969/j.issn.0258-2724.20240124
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Accurate and uninterrupted position information is crucial for ensuring the safe and efficient operation of rail transit trains. However, realizing seamless and precise positioning still poses a significant challenge for current train positioning systems operating in complex environments such as tunnels, elevated tracks, urban canyons, and suburban areas. A resilient positioning, navigation, and timing (PNT) system can produce continuous, reliable, and robust position information by integrating diverse PNT information sources. It can withstand hazards, adapt to risks, and counteract interference, offering a viable solution to the aforementioned challenges and demonstrating significant potential in fields such as military defense and aerospace. To promote the application and development of this technology in the rail transit sector, the navigation, positioning, and timing requirements of users of the rail transit industry were analyzed. According to the existing navigation and positioning capabilities of rail transit systems, the concept and framework of a resilient PNT system tailored for rail transit was proposed. Given the unique characteristics of rail transit PNT, the fundamental characteristics and evaluation metrics of the resilient PNT system of rail transit were summarized, and the relationship between resilience and accuracy, integrity, continuity, availability, and other indicators was elaborated. On the basis of multi-source PNT sensors (including global navigation satellite system (GNSS), responders, 5G-new radio (5G-R), etc.), the key technologies of the resilient PNT technology system and information fusion for rail transit were discussed. In conclusion, deep fusion of multi-source information and resilient fusion architecture are important research directions for achieving continuous seamless positioning in future rail transit.
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