Fangjun Luan
Papers
3
Total Citations
21
H-Index
3
About
Fangjun Luan is a researcher focused on advancing sensor fusion, localization, and environmental perception for autonomous systems and the Internet of Things (IoT). His work centers on improving the accuracy and robustness of state estimation in complex, uncertain environments. Luan’s major contributions include developing an enhanced Strong Tracking UKF-SLAM approach that integrates three-position ultrasonic detection to significantly improve simultaneous localization and mapping (SLAM) performance. He also proposed a DSmT-based ultrasonic detection model to estimate indoor environment contours, effectively handling uncertainties in sensor ranging and direction angle. His research extends to mobile localization in IoT, where he introduced a robust extended Kalman filter combined with improved M-estimation to mitigate the effects of non-line-of-sight propagation. With his most-cited works accumulating over 20 citations, Luan’s impact is evident in advancing practical solutions for indoor navigation and wireless sensor networks. His notable achievements include addressing fundamental challenges in sensor uncertainty and non-line-of-sight errors, making his work valuable for researchers and engineers developing reliable autonomous systems and smart environment technologies.
Research Focus
Key Achievements
Top Papers
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