High-Fidelity Reconstruction of Approach Deviations: Integrating QAR Flight Data with ILS Electromagnetic Signal Physics
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Abstract:
Precise detection of flight path deviations during the approach phase is critical for identifying operational risks and enhancing aviation safety. However, existing monitoring methods often face significant challenges in distinguishing between environmental signal distortions and operational handling errors due to the lack of high-fidelity physical reference models. To address these limitations, this study establishes an integrated simulation framework for required navigation performance (RNP) and instrument landing system (ILS) approaches by synthesizing quick access recorder (QAR) data with rigorous navigation modeling. A site-specific “digital twin” of Linfen Yaodu Airport is constructed, incorporating 3D trajectory reconstruction based on Mercator projection and Baro-VNAV logic, alongside an electromagnetic simulation of ILS signals utilizing antenna array and image theory to model multipath effects. Empirical validation demonstrates that the model accurately reproduces critical signal characteristics, including interference fringes and secondary glide slope lobes. Furthermore, quantitative regression analysis establishes a definitive linear correlation (R2>0.98) between the theoretical difference in depth of modulation (DDM) and the pilot-observed distance off track (DOT), providing a verified calibration equation for interpreting cockpit indications. The practical utility of the framework is substantiated through the investigation of a specific vertical deviation anomaly, where the model successfully traces the causal chain from signal distortion to unsafe landing parameters such as threshold height exceedance and flare compression. This research offers a robust, data-driven methodology for continuous flight quality monitoring and provides a scientific foundation for identifying the root causes of navigation incidents.
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This work was supported by the National Natural Science Foundations of China (Nos. U2333202,52272351) and the Civil Aviation Capacity Building Fund Project (No. ASSA2024/121).
LIU Jiming, GAO Zhenxing, LI Yue. High-Fidelity Reconstruction of Approach Deviations: Integrating QAR Flight Data with ILS Electromagnetic Signal Physics[J]. Transactions of Nanjing University of Aeronautics & Astronautics,2026,(2):187-202