Multi-nodal Cubic Gradiometric Array for MagNav A-PNT
Jay Trojan, Joe Miller, Davy Figaro, George Hsu, PNI Sensor
Location: Room 6-8
Date/Time: Tuesday, Jun. 4, 10:50 a.m.
The AIr Force’s future multi-domain battlefield dynamics of 2030 and 2040 necessitate robust resilience against Electronic Warfare (EW) attacks targeted at Position Navigation and Timing (PNT). The ongoing conflict in Ukraine has underscored the importance of PNT as a critically contested domain, vulnerable to peer state adversaries like China and Russia.
Recently the Department of the Air Force-Massachusetts Institute of Technology Artificial Intelligence Accelerator, or AIA, MagNav project recently performed a successful real-time in-flight magnetic navigation, or MagNav, on the C-17A Globemaster III using Scalar magnetometers. These Scalar magnetometers currently used for MagNav measures the magnetic field only at the point of its sensing element and only provides the field’s magnitude but not direction.
PNI Sensor will present feasibility results in applying the much smaller size, weight and power of PNI’s 3-axis RM3100 vector magnetometer in an alternative MagNav system that has many more magnetic sensors than the current Scalar magnetometer version. The solution is comprised of a multitude of ½ cubic inch sensor nodes in a dense, three-dimensional Cubic Gradiometric Array (CGA), where each node measures not only the magnetic field magnitude at its own spatial position, but also the field’s vector direction as well. Such a configuration provides many more dimensions of magnetic field information than a single Scalar magnetometer alone can.
Array sizes can be varied for different platforms. A 5x5x5 Cubic Gradiometric Array (CGA) would contain 125 vector magnetometers which would enable far greater capability than the handful of Scalar magnetometers used in current MagNav implementations – there would be much more insightful data for the AI calibration and positioning neural network to learn from and act upon. For example, the Cubic Gradiometric Array (CGA) can simultaneously measure multiple spatially separated points of the 3D magnetic field thus enabling the determination of the curvatures of each of the constituent layers of all superimposed fields. These can then be attributed to and corrected for each of the contributing sources of errors such as Aircraft magnetic noise and interference, as well as crustal magnetic field variations caused by measurements at different altitudes. This will greatly enhance MagNav deployability.