Neural Differential Models for Magnetic Navigation

There are several different GPS-alternatives being researched across the DoD and civilian sectors to address a GPS alternative; however, each alternative comes with additional costs and use cases. Magnetic Navigation presents an alternative GPS system that relies on magnetic resonance of the Earth – a system that is largely known and unchanging – to navigate. Some of the current problems with magnetic navigation involve 1) reducing excess noise on the system, such as magnetic outputs from the Aircraft itself, 2) determining position at a real-time pace or speeds consistent with military systems, and 3) combining with other systems to present a full-alternative GPS system.  The present project looks into using robust neural differential models to solve magnetic navigation shortcomings and provide a viable alternative to GPS.

Published Research

To learn more about Neural Differential Models for Magnetic Navigation research and other AI Accelerator projects, view our published research here.

Are you up for a Challenge?

Modern deep learning approaches show promising results in cleaning noisy signals recorded from sensors on operational aircraft. The DAF-MIT AI Accelerator is working to rapidly develop new approaches to these challenges. The AIA is seeking collaborators from across the globe to try their hand at improving on our baseline models by participating in the MagNav Open Challenge. The Challenge provides explanatory introductions to magnetic navigation, a novel "machine learning ready" dataset, starter code, and more. Get started by checking out our unique dataset and resources here.