Date of Award

3-2021

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Robert Leishman, PhD

Abstract

Alternative navigation is an area of research which employs a variety of sensor technologies to provide a navigation solution in Global Navigation Satellite System degraded or denied environments. The Autonomy and Navigation Technology Center at the Air Force Institute of Technology has recently developed the Autonomous and Resilient Management of All-source Sensors (ARMAS) navigation framework which utilizes an array of Kalman Filters to provide a navigation solution resilient to sensor failures. The Kalman Filter array size increases exponentially as system sensors and detectable faults are scaled up, which in turn increases the computational power required to run ARMAS in areal-world application. In an effort to engineer a real-time ARMAS system, this study developed C CPU and GPU versions to examine the performance trade-offs as system sensors and detectable faults are scaled up. Results show promise that a real-time ARMAS system can be achieved for large scale applications through parallel processing on a many-core processor architecture.

AFIT Designator

AFIT-ENG-MS-21-M-079

DTIC Accession Number

AD1134700

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