Date of Award
3-2023
Document Type
Thesis
Degree Name
Master of Science
Department
Department of Electrical and Computer Engineering
First Advisor
Clark N. Taylor, PhD
Abstract
In recent times, there is a great demand for resilient and robust PNT solutions. Current navigation systems rely heavily on GNSS to provide this solution. This dependence is a major concern and therefore it is prudent to use additional aids to provide the best solution possible. However, traditional methods to address this need require a nontrivial number of Kalman filters to maintain a fault-free solution. The federated filter approach provides an attractive alternative to the current solutions. In this thesis, we examine the use of the federated filter design to address this need in today’s integrated navigation systems. We compared the performance of this concept with ARMAS under normal and simulated sensor failure conditions. We also devised a re-admission process of local sensors in case of temporary failures.
AFIT Designator
AFIT-ENG-MS-23-M-023
Recommended Citation
Fernandes, Flavio, "Comparison of Federated Kalman Filter and Autonomous Resilient Management of All-source Sensors (ARMAS) Framework for Fault Detection and Exclusion" (2023). Theses and Dissertations. 6924.
https://scholar.afit.edu/etd/6924
Comments
A 12-month embargo was observed.
Approved for public release. Case number on file.