The aim of this study is to carry out an analysis of flight data anomalies and propose a flight data anomaly detection model. First, we elaborate the establishment of the motion model and the anomaly identification method, and emphasize the potential application of the method in flight data anomaly detection. Through this method, we successfully recognized multiple flight data anomaly patterns. Subsequently, we conducted a statistical analysis for the anomalous data in order to fully understand the characteristics and distribution patterns of the anomalous data. Through statistical analysis, we not only confirmed the existence of anomalous data, but also revealed significant differences between anomalous data and normal flight data. These results provide us with important clues to deeply understand the anomalies of the flight data and provide useful support for flight safety and data analysis.
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Wang et al. (2024) studied this question.
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