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Electromagnetic Interference Estimation Via Conditional Neural Processing, Edgar E. Gomez
Electromagnetic Interference Estimation Via Conditional Neural Processing, Edgar E. Gomez
Theses and Dissertations
The goal of this thesis is to determine the efficacy of employing Machine Learning (ML) to solve Joint Urgent Operational Need (JUON) CC-0575, which aims to develop a Common Operating Picture (COP) of the Global Positioning System (GPS) Electromagnetic Interference (EMI) environment. With the growing popularity of Artificial Neural Networks (ANNs), ML solutions are quickly gaining traction in businesses, academia and government. This in turn allows for problem solutions that were previously inconceivable using the classical programming paradigm. This thesis proposes a method to develop a COP of the battlefield via ANN ingestion of multiple-source signals and sensors. We conduct …
Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry
Signal Quality Monitoring Of Gnss Signals Using A Chip Shape Deformation Metric, Nicholas C. Echeverry
Theses and Dissertations
The Global Navigation Satellite System continues to become deeply em-bedded within modern civilization, and is depended on for confident, accurate navigation information. High precision position and timing accuracy is typically achieved using differential processing, however these systems provide limited compensation for distortions caused by multi-path or faulty satellite hardware. Signal Quality Monitoring (SQM) aims to provide confidence in a receivers Position, Navigation, and Timing solution and to offer timely warnings in the event that signal conditions degrade to unsafe levels. The methods presented in this document focus on implementing effective SQM using low-cost Commercial Off-the-Shelf equipment, a Software Defined Radio, …