中国民航大学学报 ›› 2023, Vol. 41 ›› Issue (4): 23-28.

• 民用航空 • 上一篇    下一篇

基于改进KNN检测的ADS-B轨迹插补研究

靳慧斌a,冯朝辉a,张召悦b,王志森b   

  1. (中国民航大学a.安全科学与工程学院;b.空中交通管理学院,天津300300)
  • 收稿日期:2021-09-06 修回日期:2021-12-29 出版日期:2023-08-25 发布日期:2023-10-25
  • 基金资助:
    中国民航大学研究生科研创新基金项目(10502756)

Research on ADS-B trajectory interpolation based on improved KNN detection

JIN Huibina , FENG Chaohui a , ZHANG Zhaoyueb , WANG Zhisenb   

  1. (a. College of Safety Science and Engineering; b. College of Air Traffic Management, CAUC, Tianjin 300300, China)
  • Received:2021-09-06 Revised:2021-12-29 Online:2023-08-25 Published:2023-10-25

摘要: 针对广播式自动相关监视(ADS-B,automaticdependentsurveillancebroadcast)地面接收站数据存在缺失点、离群点等异常点的问题,在建立多约束条件判别模型的基础上筛选ADS-B轨迹缺失点,并对航迹进行插值,采用标准化欧氏度量的改进邻近算法对整条轨迹进行异常点数据检测,最后应用多重插补法对异常轨迹点进行修复。以实际运行数据为例,验证对比了改进的K最近邻(KNN,K-nearestneighbor)算法用于检测ADS-B异常轨迹点的准确率,该方法可有效解决轨迹异常点检测疏漏问题,为航空器ADS-B原始轨迹数据挖掘提供支撑。

关键词: font-size:15.04px, ">ADS-B数据筛选;异常点检测;标准化欧氏度量;改进邻近算法;多重插补方法

Abstract: Aiming at the problem of anomalous points such as missing points and outliers in the data of automatic dependent surveillance broadcast (ADS-B) ground receiving station, the missing points of ADS-B trajectory are screened on the basis of establishing a multi-constraint discriminant model, and the trajectory is interpolated. The improved neighbor algorithm with standardized Euclidean metric is used to detect anomalous point data of the whole trajectory. Finally, the multiple interpolation method is applied to repair the anomalous trajectory points. Taking actual operational data as an example, the accuracy of the improved K-nearest neighbor (KNN) for detecting ADS-B anomalous trajectory points is verified and compared. This method can effectively solve the problem of detection omission of trajectory anomalous point and provide support for mining original trajectory data of aircraft ADS-B.

Key words: ADS-B data screening, anomalous point, standardized Euclidean metric, improved neighbor algorithm, multiple interpolation method

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