Vector Tracking Loop for GPS and Galileo Receiver Combined with Machine Learning Multi-Path and Non-Line-of-Sight Detectors and Fusion with IMU for Autonomous Vehicle

Martin Bransby, Pekka Peltola, Smita Tiwari, Katie Roll, Ben Lavin, Louise Mercy, Ivan Petrunin, Zhengjia Xu, Teng Li, Nicolas Giron

Peer Reviewed

Abstract:	Autonomous driving relies on multiple complementary sensors. GNSS receivers provide the basis for absolute positioning. Though, under canopy and in urban environments, positioning errors are too large. Inertial mechanisation and camera-based positioning fusion aid, in GNSS achieving higher accuracy. Although these come with their disadvantages. Ultrasound sensors may probe through rain where cameras and conventional LIDARs see a wall. Lane level positioning necessitates improvement of the available technologies, including making inertial sensors more accurate and developing better models for car application constraints. Further, cameras play an important role, although being resource heavy. Finally, our focus in this work, the GNSS ranging improvement needs better integrity. Cranfield University and central London test drives were conducted to test the developed GPS and Galileo vector tracking receiver with SNR, elevation, multipath and non-line-of-sight detectors. The results of this work, performed under ESA NAVISP EL1 066 project VTL4AV, show the way forward in making GNSS ranging more robust and reliable with the developed advanced channel monitoring strategy.
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:	2183 - 2197
Cite this article:	Bransby, Martin, Peltola, Pekka, Tiwari, Smita, Roll, Katie, Lavin, Ben, Mercy, Louise, Petrunin, Ivan, Xu, Zhengjia, Li, Teng, Giron, Nicolas, "Vector Tracking Loop for GPS and Galileo Receiver Combined with Machine Learning Multi-Path and Non-Line-of-Sight Detectors and Fusion with IMU for Autonomous Vehicle," Proceedings of the 38th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2025), Baltimore, Maryland, September 2025, pp. 2183-2197. https://doi.org/10.33012/2025.20476
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