基于黎曼距离的编队飞行卫星姿态控制系统故障检测数据优选方法

为突破星上资源的严苛约束、提升编队飞行卫星故障检测能力，提出了一种适用于编队飞行卫星姿态控制系统的故障检测数据优选方法，通过利用黎曼距离衡量无故障情况和故障情况下系统测量信息之间的差距，构建了编队飞行卫星姿态控制系统故障检测能力的评价指标。在此基础上，提出了故障检测数据优选方法，为系统输出信息结构优化提供了理论依据。仿真表明，所提出的方法能够在星上资源受限的情况下有效提升编队飞行卫星姿态控制系统的故障检测能力。

Riemann Distance-Based Fault Detection Data Selection Method for Formation Flying Satellite Attitude Control Systems

To overcome the stringent constraints of on-board resources and improve the fault detection capabilities of formation flying satellites, a Riemann distance-based fault detection data selection method applicable to the attitude control system of formation flying satellites is proposed. The Riemann distance measures the difference between the system''s measurement information under fault-free and fault conditions. This is used to establish an evaluation index, which assesses the fault detection capability of the formation flying satellite attitude control system. On this basis, a fault detection data selection method is proposed, providing a theoretical foundation for the optimization of the system output information structure. The simulation has shown that the proposed method can effectively enhance the fault detection capability of the formation flying satellite attitude control system under the condition of limited on-board resources