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Full-Text Articles in Engineering
Improving Aeromagnetic Calibration Using Artificial Neural Networks, Mitchell C. Hezel
Improving Aeromagnetic Calibration Using Artificial Neural Networks, Mitchell C. Hezel
Theses and Dissertations
The Global Positioning System (GPS) has proven itself to be the single most accurate positioning system available, and no navigation suite is found without a GPS receiver. Even basic GPS receivers found in most smartphones can easily provide high quality positioning information at any time. Even with its superb performance, GPS is prone to jamming and spoofing, and many platforms requiring accurate positioning information are in dire need of other navigation solutions to compensate in the event of an outage, be the cause hostile or natural. Indeed, there has been a large push to achieve an alternative navigation capability which …
Convolutional Neural Network Architecture Study For Aerial Visual Localization, Jedediah M. Berhold
Convolutional Neural Network Architecture Study For Aerial Visual Localization, Jedediah M. Berhold
Theses and Dissertations
In unmanned aerial navigation the ability to determine the aircraft's location is essential for safe flight. The Global Positioning System (GPS) is the default modern application used for geospatial location determination. GPS is extremely robust, very accurate, and has essentially solved aerial localization. Unfortunately, the signals from all Global Navigation Satellite Systems (GNSS) to include GPS can be jammed or spoofed. To this response it is essential to develop alternative systems that could be used to supplement navigation systems, in the event of a lost GNSS signal. Public and governmental satellites have provided large amounts of high-resolution satellite imagery. These …
Navigation With Artificial Neural Networks, Joseph A. Curro Ii
Navigation With Artificial Neural Networks, Joseph A. Curro Ii
Theses and Dissertations
The objective of this dissertation is to explore the applications for Artificial Neural Networks (ANNs) in the field of Navigation. The state of the art for ANNs has improved significantly so now they can rival and even surpass humans in problems once thought impossible. We present different methods to augment, combine, or replace existing Navigation filters with ANN. The main focus of these methods is to use as much existing knowledge as possible then use ANNs to extend the current knowledge base. Next, improvements are made for a class of Artificial Neural Network (ANN)s which provide covariance called Mixture Density …