Date of Award

3-2022

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Robert C. Leishman, PhD

Abstract

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.

AFIT Designator

AFIT-ENG-MS-22-M-073

DTIC Accession Number

AD1166934

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