FlightMagNav: An Open Dataset and Probabilistic Map Learning and Validation Framework for Outdoor Magnetic Field-Based Positioning

Abstract:Magnetic field-based positioning is a resilient positioning technology that requires no external infrastructure and is hard to jam at scale. To facilitate research on magnetic field-based positioning for aerial platforms operating close to the Earth's surface, an open dataset is presented with measurements collected using an unmanned aerial vehicle carrying two optically pumped magnetometers, a type of quantum magnetometer, and a global navigation satellite system-aided inertial navigation system. The dataset includes measurements for both magnetic-field map learning and validation. Along with the dataset, a probabilistic framework for magnetic-field map learning and validation is presented and used to illustrate how the dataset may be used. Finally, we outline research directions that may be explored using the dataset.

Signal Processing (eess.SP); Robotics (cs.RO)

arXiv:2610.08982 [eess.SP]

(or arXiv:2610.08982v1 [eess.SP] for this version)

https://doi.org/10.48550/arXiv.2610.08982 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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