A Fault Detection and Isolation (FDI) algorithm is developed to protect against Water-Blockage (WB) pitot tube failure in the safety-critical Air Data System (ADS) used on small Unmanned Aircraft Systems (UAS). The algorithm utilizes two identical Synthetic Air Data Systems (SADS) as the basis for state estimation. Each SADS works independently with a pitot tube while sharing an IMU and GNSS receiver. The fault detection is designed using the integrity monitoring framework, and the isolation is obtained via independent fault detection channels. The ADS requirements are established, and the WB failure mode is analyzed based on real faulty air data. A new residual-based test statistic is introduced, and the link among the test statistic, observability matrix, and Minimal Detectable Error (MDE) are examined. Finally, a flight data set with a known water-blockage fault signature is used to assess the algorithm's performance in terms of the air data protection levels and alert limits.

中文翻译：

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使用完整性监控框架的小型无人机航空数据故障检测和隔离

开发了一种故障检测和隔离 (FDI) 算法，以防止小型无人机系统 (UAS) 上使用的安全关键空气数据系统 (ADS) 中出现水堵塞 (WB) 皮托管故障。该算法利用两个相同的合成空气数据系统 (SADS) 作为状态估计的基础。每个 SADS 与皮托管独立工作，同时共享 IMU 和 GNSS 接收器。故障检测采用完整性监控框架设计，通过独立的故障检测通道获得隔离。建立了 ADS 要求，并基于真实的故障空气数据分析了 WB 故障模式。引入了一种新的基于残差的检验统计量，并检验了检验统计量、可观察性矩阵和最小可检测误差 (MDE) 之间的联系。最后，