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Belief reliability modeling of coarse tracking system for satellite optical communication

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  • Tao, Zhao
  • Chen, Wenbin
  • Li, Xiaoyang
  • Kang, Rui

Abstract

Coarse tracking system is an important part of satellite optical communication terminals, which uses feedback control to perform its function of the coarse alignment of beacon light, so its tracking accuracy is particularly critical. Under long-time operation, there are degradation and uncertainties affecting the tracking accuracy, which further causes reliability reduction. However, current research has not described the above relationship between the reliability of the coarse tracking system and the factors, including the function principle of feedback control, degradation, and uncertainties. In this work, the control theory and reliability science principles are combined for the reliability modeling of a coarse tracking system. First, we build up the performance margin equation of tracking accuracy for a coarse tracking system, which is characterized by a control block diagram model. Then, we construct the margin degradation equation by characterizing the combined effects of component degradations. Finally, we analyze and quantify the uncertainties, and give the reliability function of the coarse tracking system. The proposed model is applied to a real case. The corresponding results show that the proposed method can identify the critical components, the sensitive design parameters, and the main uncertainty sources, which can directly guide the design of the coarse tracking system.

Suggested Citation

  • Tao, Zhao & Chen, Wenbin & Li, Xiaoyang & Kang, Rui, 2025. "Belief reliability modeling of coarse tracking system for satellite optical communication," Reliability Engineering and System Safety, Elsevier, vol. 256(C).
    • Handle: RePEc:eee:reensy:v:256:y:2025:i:c:s0951832024008342
    DOI: 10.1016/j.ress.2024.110763
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    References listed on IDEAS

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    1. Chen, Shi-Shun & Li, Xiao-Yang, 2026. "A new moment-independent uncertainty importance measure based on cumulative residual entropy for developing uncertainty reduction strategies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 239(C), pages 263-281.
    2. Wang, Cong & Chen, Yunxia & Zheng, Jiawei & Zhou, Yuan, 2025. "System reliability analysis based on non-parametric modeling and melding of multi-source data," Reliability Engineering and System Safety, Elsevier, vol. 262(C).

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