Flight data-driven modeling has become an important approach for trajectory prediction, anomaly detection, and risk assessment in unmanned aerial vehicles and other aerial systems. Such data are usually high-dimensional, nonlinear, multirate, and non-stationary, especially during maneuvering flight, environmental distu...
Fang Wang, Tianjing Liu, Yongzheng Wang et al.· Electronics· 0 citations
This paper reviews QAR data-driven methods for flight anomaly detection and risk warning from the perspective of statistical learning and aviation data science and provides a structured reference for using QAR data to support aviation safety assessment, risk warning, and operational decision-making.
Fang Wang, Yixin Zhang, Yongzheng Wang et al.· Aerospace· 0 citations
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