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Workshop: NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences

Physics-Informed Calibration of Aeromagnetic Compensation in Magnetic Navigation Systems using Liquid Time-Constant Networks

Favour Nerrise · Andrew Sosanya · Patrick Neary


Magnetic navigation is a rising GPS alternative that has proven useful for airborne magnetic navigation (MagNav). External magnetic fields combine Earth’s crustal anomaly field and disruptions induced by aircraft electronics and Earth’s large-scale magnetic fields. We introduce an approach using Liquid Time-Constant Networks (LTCs) to minimize noise observed in airborne MagNav. LTCs can effectively model and remove the aircraft’s magnetic interference, improving the detection of weak anomalies. Using real flight data, we compare our system to traditional models and observe up to a 64% reduction in aeromagnetic compensation error (RMSE nT). This indicates our proposed approach can significantly improve the efficiency and reliability of airborne MagNav.

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