As a typical safety-critical system, satellite has extremely stringent requirements for reliability. However, some satellite components, especially attitude sensors, are prone to suffer from performance degradation or even drastic failure in space environment, which leads to serious threats to satellite. A series of fault diagnosis methods have been investigated to diagnose these failures. However, due to the increasingly complex structure and various operating conditions of satellite, it is still a challenging task to diagnose attitude sensor failures robustly and reliably. In addition, sophisticated diagnosis methods result in heavy calculations, which may not satisfy satellite autonomy requirements. Given these issues, this article proposes an integrated fault detection, isolation, and reconstruction (FDIR) scheme for attitude sensors, such as fiber-optic gyroscopes (FOGs) and star sensor, using an adaptive hybrid method. The parity equation (PE) approach is applied to detect gyros fault. On the basis of attitude kinematics model and sensor measurement equation, a novel adaptive extended Kalman filter (EKF) is developed simultaneously. Then, the chi-square test is established using an innovation sequence for detecting sensor fault. According to fault detection results, different reconstruction strategies are presented by autonomously tuning noise covariance parameters, which will be used to reconstruct the faults of gyros and star sensor. Combined with the PE approach and chi-square test, faults in gyroscopes and star sensor can be detected reliably. Then, using this adaptive algorithm, these failures can be isolated and reconstructed accurately. Finally, the effectiveness of the presented method is verified by simulating typical faults of gyros and star sensor.

中文翻译：

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使用自适应混合方法的卫星姿态传感器故障检测、隔离和重建


卫星作为典型的安全关键系统，对可靠性有着极其严格的要求。然而，卫星的一些部件，特别是姿态传感器，在太空环境中很容易出现性能下降甚至严重失效的情况，对卫星造成严重威胁。人们研究了一系列故障诊断方法来诊断这些故障。然而，由于卫星结构日益复杂，运行条件​​多样，​​稳健可靠地诊断姿态传感器故障仍然是一项具有挑战性的任务。此外，复杂的诊断方法导致计算量大，可能无法满足卫星自主性要求。鉴于这些问题，本文提出了一种采用自适应混合方法的姿态传感器（例如光纤陀螺仪（FOG）和星传感器）的集成故障检测、隔离和重建（FDIR）方案。应用奇偶校验方程（PE）方法来检测陀螺仪故障。在姿态运动学模型和传感器测量方程的基础上，同时开发了一种新型自适应扩展卡尔曼滤波器（EKF）。然后，使用创新序列建立卡方检验来检测传感器故障。根据故障检测结果，通过自主调整噪声协方差参数提出不同的重构策略，用于陀螺仪和星敏感器的故障重构。结合PE方法和卡方检验，可以可靠地检测陀螺仪和星敏感器的故障。然后，使用这种自适应算法，可以准确地隔离和重建这些故障。最后通过对陀螺仪和星敏感器典型故障的仿真验证了该方法的有效性。