CubeSats and their on-board computers: Systematic literature review
Heading:
| 1Liubimov, OV, 1TurkinI., IB 1National Aerospace University “Kharkiv Aviation Institute”, Kharkiv, Ukrain |
| Space Sci. & Technol. 2025, 31 ;(6):014-037 |
| https://doi.org/10.15407/knit2025.06.014 |
| Publication Language: English |
Abstract: CubeSats have revolutionized the exploration and utilization of near-space environments, particularly in low-earth orbit. In this
study, we present a systematic review of the current literature to identify and discuss the main developments, research circle, and advancements in the development of nanosatellite avionics, with a focus on onboard computers, covering both hardware and software aspects. A systematic literature review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Out of the 647 articles extracted from Science Direct and IEEE, 202 studies were selected based on rigorous inclusion and exclusion criteria, revealing six major thematic areas in nanosatellite design and operation. The findings are organizedinto six subsections that address the most frequently discussed items in designing, developing, and operating nanosatellites. The listof topics begins with the onboarding of the mission’s analysis and overview and continues with the review of hardware and software solutions for the onboard computers, their architecture and reliability assessment, and the system engineering surrounding them. The review concludes with two applied directions for telemetry and communication, as well as the use of machine learning onboard nanosatellites. According to the results, CubeSat research and development continue growing rapidly, leveraging modern embedded technology advancements. The availability, robustness, and high integration level of commercial off-the-shelf components have brought graphics processing units, field-programmable gate arrays, and multi-core computing systems into space. These powerful and energy-efficient computers, reinforced by modern machine learning models, enable the rapid and reliable development of complex, sophisticated missions. Finally, the conclusions highlight the major findings, potential future trends, and research topics in the field. Ultimately, this article serves as a comprehensive guide for scientists, developers, integrators, and enthusiasts engaged in space technology research and development.
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| Keywords: AI, Command and Data Handling Module, COTS, CubeSat, hardware, machine learning, nanosatellites, On-Board Computer, reliability, software, system engineering, systematic literature review |
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