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
The ARMAS framework was created with the goal of developing a framework for all-source sensors which is able to combine detection, identification, calibration, model selection, and independent evaluation into a single system. Stable Observability Monitoring (SOM), augments the original ARMAS framework by enabling ARMAS to detect whether or not its Fault Detection and Exclusion (FDE) capabilities can be trusted and when additional sensor information is required to maintain resiliency. While previously tested with simulated sensor data, SOM has yet to be tested with real-life sensor data. Furthermore, ARMAS has only been tested with real-life GNSS data. This work expands on previous work by testing the ARMAS-SOM framework with real-life GPS, ranging radio, and camera sensor data, while analyzing its strengths and weaknesses.
AFIT Designator
AFIT-ENG-MS-22-M-009
DTIC Accession Number
AD1166830
Recommended Citation
Blakely, Brandon M., "Evaluation of the ARMAS-SOM Framework with Real Data" (2022). Theses and Dissertations. 5366.
https://scholar.afit.edu/etd/5366