The ability to use GPS for navigation is becoming increasingly limited in certain areas of the world. Knowing this, the Air Force Research Labs is constantly looking for ways to improve alternate navigation methods such as magnetic navigation. In the interest of making advancements in aircraft disturbance xC;field modelling, Lieutenant Emery recreates models from previous works to prove results. Lieutenant Emery also introduces a novel model architecture that attempts to mix the xC;filtering properties of Tolles-Lawson with the non-linear capabilities of an artifixC;cial neural network. The introduction of this model could present better aircraft disturbance xC;field modelling and in turn, more reliable magnetic navigation in regions where GPS is not available.
Modelling Aircraft Disturbance Fields for Magnetic Navigation Using Dense ANNs and the Novel MANNTL Architecture
2021
80 pages
Report
Keine Angabe
Englisch
Computers, Control & Information Theory , Navigation Systems , Air force , Aircrafts , Artificial intelligence software , Convolutional neural networks , Global positioning systems , Information science , Machine learning , Magnetic fields , Magnetic navigation , Magnetometers , Measurement , Military research , Navigation , Neural networks , Supervised machine learning , United states , Unmanned aerial vehicles
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