Albert recently received his PhD from MIT AeroAstro and is now a postdoc in the Julia Lab within MIT CSAIL. His research is focused on improving airborne magnetic anomaly navigation using machine learning-based aeromagnetic compensation approaches (and the Julia programming language). Albert received his B.S. degree in mechanical engineering from UW–Madison in 2015 and S.M. degree in aeronautics and astronautics from MIT in 2018. Albert previously worked on electric aircraft design as an NSF graduate research fellow, and he earned his private pilot license in 2020.
MagNav.jl is an open-source Julia package that contains a full suite of tools for aeromagnetic compensation and airborne magnetic anomaly navigation. This talk will describe the high-level functionalities of the package, then provide a brief tutorial using real flight data that is available within the package. The functionalities can be divided into the four essential components of MagNav: sensors (flight data), magnetic anomaly maps, aeromagnetic compensation models, and navigation algorithms.