| dc.description.abstract | Using the earth's magnetic anomaly field for navigation of aircraft has shown promise as a viable alternative to the Global Positioning System (GPS) and other navigation systems. An airborne magnetic anomaly navigation (MagNav) system collects real-time magnetic field data and uses predetermined magnetic anomaly maps of the earth to estimate location by aiding an inertial navigation system (INS), which continually drifts. MagNav has the benefits of being passive, globally available at all times and in all weather, and not reliant on sight of land or stars. Since the magnetic field strength of a dipole decreases with the inverse cube of distance, MagNav is also nearly unjammable. A corrupting magnetic source must be flying alongside or in the aircraft to be effective.
This magnetic physics has other implications, though. In particular, the magnetic components of the aircraft itself interfere with the desired magnetic measurements that are required to navigate. Magnetic measurements are a linear superposition of multiple magnetic fields. When the measured data contains magnetic signals from both the (desired) earth field and (undesired) aircraft field, it is difficult to separate the two signals. Previous work has proven the viability of MagNav using exceedingly clean magnetic measurements taken by geo-survey aircraft. The most significant outstanding challenge for real-world, operational MagNav is handling corruption of the measured magnetic signal by magnetic sources from aircraft components.
In this thesis, several approaches to enable high-accuracy MagNav, despite receiving corrupted magnetic field measurements, are explored. These approaches can be split into four groups: linear aeromagnetic compensation, nonlinear aeromagnetic compensation, online aeromagnetic compensation, and covariance-adaptive filtering. The first two approaches evaluate different models that aim to improve on the state-of-the-art linear model used for removing aircraft interference. The last two approaches focus on making adjustments within the navigation algorithm in real-time based on the (corrupted) data provided. Performance is compared against the state-of-the-art compensation and navigation approach, which show that these advanced linear and nonlinear models can benefit MagNav when only corrupted magnetic field measurements are available. Each model and additional tools for aeromagnetic compensation and airborne magnetic anomaly navigation are publicly available in the MagNav.jl Julia software package. | |
