Analysis of Navigation Station Positioning Errors Based on QAR Data
With the development of civil aviation,airspace congestion become increasingly prevalent,high-lighting the escalating issues of safety.Civil aviation relies predominantly on ground-based navigation e-quipment for aircraft positioning,ensuring navigation along predetermined routes.Consequently,the relia-bility and accuracy of navigation equipment become paramount.Promptly identifying faulty navigation sta-tions,assessing navigation accuracy,and achieving precise positioning are imperative.Leveraging QAR data for the indirect verification of navigation stations facilitates these processes.This study employs Kal-man filtering to denoise onboard big data,utilizing coordinate transformation,spline interpolation,trajecto-ry prediction,and data fusion to obtain a nominal flat trajectory.Based on the theoretical distribution of errors,the positional error is calculated with the nominal trajectory as a reference.Subsequently,a ridge regression model is established to determine the degree of influence of each factor on errors.Furthermore,a method for measuring navigation station availability is proposed based on dynamic time warping,facilita-ting the quantification of navigation station availability and accuracy.Finally,the model is validated as ef-fective through real-world cases.
air transportationpositioning errorsQARnavigation accuracy and availabilitytrajectory fu-sion
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