DAF-MIT AIA Open Flight Data for Magnetic Navigation Research

This dataset was developed as part of the DAF-MIT Artificial Intelligence Accelerator to support research on airborne magnetic anomaly navigation (MagNav), an alternative to GPS. Flight data was collected during the summer of 2020 by Sander Geophysics Ltd. (SGL) near Ottawa, Ontario, Canada using a Cessna Grand Caravan equipped with a number of sensors.

Within the dataset is a nearly perfect signal of the Earth's magnetic field (minimal aircraft interference) from tail stinger (boom) measurements, as well as four noisy magnetic signals (varying degrees of aircraft interference) from in-aircraft measurements. These scalar measurements of the total field were generated from five optically pumped, split-beam cesium vapor magnetometers. Additionally, four fluxgate magnetometers were used for vector measurements of the total field. The dataset also contains supplemental sensor data from the inertial navigation system, GPS position data, voltages, currents, and more.

During the data collection flights, various events were purposely carried out to cause temporal magnetic field disturbances. This included control surface movements (e.g., flaps up/down), fuel pump on/off, radio use, and movement of magnetic materials within the cabin. The flight patterns and altitudes were also varied from flight to flight to provide a diverse dataset. Please see the provided datasheet for further high-level dataset information and the readmes for individual flight details.

This dataset supports the Signal Enhancement for Magnetic Navigation Challenge Problem: https://magnav.mit.edu