Date of Award
Master of Science
Department of Electrical and Computer Engineering
Robert C. Leishman, PhD
Currently, analysis on navigation systems can be slow and computationally expensive using Monte Carlo approaches. Covariance analysis is a tool that can return trade space analysis results promptly and can be computationally reasonable. This research aims to create a covariance analysis tool in a new navigation framework architecture, PntOS. The creation of this covariance tool is explained in coordination with the tool being used in a few different navigation scenarios with the results. These scenarios include a Doppler LiDAR velocity sensor and magnetic anomaly navigation.
DTIC Accession Number
Williams, Tristan T., "Covariance Analysis for Multi-Source Navigation Architecture" (2022). Theses and Dissertations. 5371.