Date of Award:

5-2026

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Electrical and Computer Engineering

Committee Chair(s)

Charles Swenson

Committee

Charles Swenson

Committee

Jonathan Phillips

Committee

Donald Cripps

Abstract

Modern small satellites often lack the ability to analyze their data in real time, relying instead on downlinking raw measurements to Earth before any scientific interpretation can occur. This delay restricts missions that require rapid awareness of environmental or space-weather events. This thesis presents the Low-power Array for Cubesat Edge Computing Architecture, Algorithms, and Applications (LACE-C3A), a hardware platform designed to enable in-orbit data processing within the power and volume limits of CubeSat-class spacecraft. 

LACE-C3A uses a modular cluster of flash-based FPGAs, which offer low power consumption, radiation resilience, and in-flight reconfigurability. The system consists of a Controller board responsible for ingesting and routing data from diverse sensors, and Pe-ripheral compute boards that execute machine-learning algorithms using dedicated memory and multi-gigabit communication links. This work focuses on the hardware design of these components, including power regulation, high-speed serial interfaces, memory subsystems, and board-to-board interconnects. 

The results demonstrate that a scalable, FPGA-based compute array can support real-time edge computing on small satellites, providing a viable path toward more autonomous and responsive spacecraft.

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Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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