Precise Tunnel Navigation and Positioning Based on Geomagnetic Matching

Pan Jiang, Chengjian Deng, DingJun Liu, Yuliang Jin, Yilong Yuan, Chang Liu

Peer Reviewed

Abstract: This paper proposes a high-precision navigation and positioning algorithm based on geomagnetic matching for tunnel environments. The algorithm utilizes data from the smartphone’s built-in gyroscope, accelerometer, and magnetometer sensors to compute real-time geomagnetic sequences, which are then matched against a pre-constructed geomagnetic fingerprint map. To enhance matching accuracy, a characteristic peak detection technique is employed to ensure the consistency of the sequences to be matched. Furthermore, the Dynamic Time Warping (DTW) algorithm is applied to address the issue of sequence length variation caused by speed errors in inertial navigation system (INS) dead reckoning. To validate the algorithm’s effectiveness, extensive field tests were conducted in over 100 tunnels across multiple cities in China, utilizing various smartphone models and vehicles. Experimental results demonstrate that the maximum positioning error within the tunnels is better than 50 meters, and the lane-level matching accuracy exceeds 90%. Currently, this algorithm has been successfully integrated into the Tencent Maps navigation system, providing users with significantly enhanced positioning services in tunnel scenarios where Global Navigation Satellite System (GNSS) signals are unavailable.
Published in: Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025)
September 8 - 12, 2025
Hilton Baltimore Inner Harbor
Baltimore, Maryland
Pages: 1695 - 1703
Cite this article: Jiang, Pan, Deng, Chengjian, Liu, DingJun, Jin, Yuliang, Yuan, Yilong, Liu, Chang, "Precise Tunnel Navigation and Positioning Based on Geomagnetic Matching," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 1695-1703. https://doi.org/10.33012/2025.20282
Full Paper: ION Members/Non-Members: 1 Download Credit
Sign In