Future Satellite Lifetime Prediction From the Historical Trend in Satellite Half-Lives
Venkata Jaipal Reddy Batthula, Richard S. Segall, Daniel Berleant, Hyacinthe Aboudja, Peng-Hung Tsai
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Venkata Jaipal Reddy Batthula
Department of Information Science, University of Arkansas at Little Rock, Little Rock, Arkansas, United States
Richard S. Segall
Department of Information Systems & Business Analytics, Arkansas State University, State University, Arkansas, United States
Daniel Berleant
Department of Information Science, University of Arkansas at Little Rock, Little Rock, Arkansas, United States
Hyacinthe Aboudja
Department of Computer Science & Mathematics, Oklahoma City University, Oklahoma City, Oklahoma, United States
Peng-Hung Tsai
Department of Information Science, University of Arkansas at Little Rock, Little Rock, Arkansas, United States
Cite this paper as:Batthula, V. J. R., Segall, R. S., Berleant, D., Aboudja, H., Tsai, P. (2022). Future Satellite Lifetime Prediction From the Historical Trend in Satellite Half-Lives.
Journal of Systemics, Cybernetics and Informatics, 20(3), 40-45. https://doi.org/10.54808/JSCI.20.03.40
Online ISSN (Journal): 1690-4524
Abstract
Satellite lifetime is one of the important characteristics of satellite design and construction. It’s also of practical importance to know when a satellite is about to fail, as reentry and disposal can become operational matters. Satellite lifetime estimation is not necessarily a one-time action, but can be repeated, and it depends on many factors such as orbital parameters, operational requirements, and various others.
Many products today are designed with safety, quality, and service life in mind. Based on the historical trend in satellite lifetimes, the approach used here is to predict the lifetimes of satellites using half-life values of their launch year cohorts. Half-life calculations can be made using either launch year or failure year cohorts, making a comparison of these of interest in forecasting the future lifetimes of satellites.
This study focuses on analyzing satellite half-lives and using that information to project lifetimes of satellites that are still operational from the satellite launch year. We examine conformance of satellite lifetime data to fitted curves that remove noise from the data and thereby predict lifetimes of satellites from their launch year cohorts.
