10.2514/6.2023-72153">
 

Statistical Reliability Estimation for Deep Space Satellites: 1991-2023

Document Type

Conference Proceeding

Publication Date

1-1-2023

Abstract

Reliability analysis using satellite failure data for deep space satellites launched in the years 1991-2023 is presented. Relevant satellite performance information is obtained using the Seradata database, which is an open-source intelligence database on international satellites. This data includes launch information, anomaly details, and failure identification. A performance window of 1991-2023 with respect to satellite launch date is utilized to define the dataset to include all presently available contemporary data. The reliability analysis is completed using nonparametric and parametric methods. The Kaplan-Meier estimator is utilized to derive a nonparametric reliability estimate from the raw, censored failure data. The Weibull distribution is utilized for parameterization of the predicted reliability and performance analysis. Two methods for fitting the Weibull distribution to the estimated reliability are explored in this work, those being a graphical method and maximum likelihood estimation. The results from the two methods are compared by examining the Weibull distributions' agreement with the nonparametric reliability estimate. With the reliability estimate parameterized, the results are extended out to larger time windows to predict the theoretical reliability of satellites with longer lifetimes. Results show a relatively low reliability for deep space satellites over 15 years of performance data with a high degree of infant mortality.

Comments

Copyright © 2023 by Travis M. Grile. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.

Source Publication

2023 Regional Student Conferences, Region I - North East

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