Pai Wang
Papers
2
Total Citations
5
H-Index
2
About
Pai Wang is a leading researcher in integrated sensing and communication (ISAC) systems, with a primary focus on high-precision localization for autonomous vehicles and robotics. Their work bridges the gap between 5G New Radio (NR) networks and environmental sensing, demonstrating how standard downlink pilots can be repurposed for channel impulse response-based localization. This foundational contribution, detailed in their 2025 paper, has already garnered 3 citations and establishes a theoretical framework for using cellular infrastructure as a ubiquitous sensor. Wang’s second major contribution addresses the critical challenge of urban positioning by developing a factor graph-based tightly coupled RTK/INS/LiDAR system. This work introduces a de-drifting LiDAR data association method that significantly improves accuracy and continuity in GNSS-denied environments, earning 2 citations. By tightly fusing GNSS, inertial, and LiDAR data, Wang has advanced the reliability of autonomous navigation systems. Their research is particularly notable for its practical applications in autonomous driving and mobile robotics, where robust, centimeter-level positioning is essential. Wang’s work represents a significant step toward seamless, sensor-rich environmental perception.
Research Focus
Key Achievements
Top Papers
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- 2