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A Hybrid Method Combining Improved K-means Algorithm with BADA Model for Generating Nominal Flight Profiles

A Hybrid Method Combining Improved K-means Algorithm with BADA Model for Generating Nominal Flight Profiles
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摘要 A high-precision nominal flight profile,involving controllers′intentions is critical for 4Dtrajectory estimation in modern automatic air traffic control systems.We proposed a novel method to effectively improve the accuracy of the nominal flight profile,including the nominal altitude profile and the speed profile.First,considering the characteristics of trajectory data,we developed an improved K-means algorithm.The approach was to measure the similarity between different altitude profiles by integrating the space warp edit distance algorithm,thereby to acquire several fitted nominal flight altitude profiles.This approach breaks the constraints of traditional K-means algorithms.Second,to eliminate the influence of meteorological factors,we introduced historical gridded binary data to determine the en-route wind speed and temperature via inverse distance weighted interpolation.Finally,we facilitated the true airspeed determined by speed triangle relationships and the calibrated airspeed determined by aircraft data model to extract a more accurate nominal speed profile from each cluster,therefore we could describe the airspeed profiles above and below the airspeed transition altitude,respectively.Our experimental results showed that the proposed method could obtain a highly accurate nominal flight profile,which reflects the actual aircraft flight status. A high-precision nominal flight profile, involving controllers' intent ions is critical for 4D trajectory est i-mation in modern automatic air traffic control systems. We proposed a novel method to effectively improve the accuracy of the nominal flight profile, including the nominal altitude profile and the speed profile. First, considering the characteristics of trajectory data, we developed an improved K-means algorithm. The approach was to measure the similarity between different altitude profiles by integrating the space warp edit distance algorithm, thereby to acquire several fitted nominal flight altitude profiles. This approach breaks the constraints of traditional K-means algorithms. Second, to eliminate the influence of meteorological factors, we introduced historical gridded binary data to determine the en-route wind speed and temperature via inverse distance weighted interpolation. Finally, we facilitated the true airspeed determined by speed triangle relationships and the calibrated airspeed determined by aircraft data model to extract a more accurate nominal speed profile from each cluster, therefore we could describe the airspeed profiles above and below the airspeed transition altitude, re sp ectively. Our experimental results showed that the proposed method could obtain a highly accurate nominal flight profile, which reflects the actual aircraft flight status.
出处 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2016年第4期414-424,共11页 南京航空航天大学学报(英文版)
基金 supported by the National Natural Science Foundation of China(Nos.61174180,U1433125) the Jiangsu Province Science Foundation (No.BK20141413) the Chinese Postdoctoral Science Foundation (No.2014M550291)
关键词 air transportation flight profile K-means algorithm space warp edit distance(SWED)algorithm trajectory prediction air transportation flight profile K-means algorithm space warp edit distance(SWED)algorithm trajectory prediction
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