This article explores and verifies the application of real-time telemetry driven prognostics and health management (PHM) methods in the guidance and navigation control (GNC) system of autonomous rendezvous and docking (RVD) spacecraft, focusing on the characteristics and predictive rapid evaluation requirements. Based on the hierarchical characteristics of GNC system composition and the fuzzy characteristics of health status, a data-driven PHM architecture, process, and method for RVD GNC tasks is proposed. By comprehensively applying fuzzy theory and analytic hierarchy process (AHP), the health status membership degree is determined step by step, and combined with the flight trajectory prediction results, the GNC system health assessment is completed. Experiments and simulations are performed to indicate that the proposed system can assist ground flight control personnel in making decisions effectively.

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Research on GNC Real-Time Health Assessment Method for Rendezvous and Docking Spacecraft Based on Telemetry Data Driven

  • Hui Hao,
  • Zongyu Liu,
  • Zengbo Liu,
  • Changqing Chen,
  • Qiang Zhang

摘要

This article explores and verifies the application of real-time telemetry driven prognostics and health management (PHM) methods in the guidance and navigation control (GNC) system of autonomous rendezvous and docking (RVD) spacecraft, focusing on the characteristics and predictive rapid evaluation requirements. Based on the hierarchical characteristics of GNC system composition and the fuzzy characteristics of health status, a data-driven PHM architecture, process, and method for RVD GNC tasks is proposed. By comprehensively applying fuzzy theory and analytic hierarchy process (AHP), the health status membership degree is determined step by step, and combined with the flight trajectory prediction results, the GNC system health assessment is completed. Experiments and simulations are performed to indicate that the proposed system can assist ground flight control personnel in making decisions effectively.