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• 民用航空 •    下一篇

基于多源异构数据的航班追踪盲区评估#br#

韩萍,张秉清,张喆,卢晓光
  

  1. taptap下载安装安卓电子信息与自动化学院,天津300300
  • 出版日期:2020-08-27 发布日期:2020-08-27
  • 作者简介:韩萍(1966—),女,天津人,教授,博士,研究方向为航空器全球追踪与监控新技术.​
  • 基金资助:
    国家重点基础研究发展计划项目(2016YFB0502405)

Flight tracking gap assessment based on multi-source heterogeneous data#br#

HAN Ping, ZHANG Bingqing, ZHANG Zhe, LU Xiaoguang#br#   

  1. College of Electronic Information Engineering and Automation, CAUC, Tianjin 300300, China
  • Online:2020-08-27 Published:2020-08-27
  • Supported by:

摘要: 针对实际飞机通信寻址报告系统(ACARS)和广播式自动相关监视(ADS-B)追踪数据在航班全球追踪过程中由信号覆盖出现的位置报告缺失问题,建立追踪盲区评估模型。首先通过三次样条插值算法对缺失报告位置进行重构,然后在评估区域内划分航迹点覆盖区域和缺失区域,基于高斯核函数的SVM 算法得到缺失区域内部的盲区位置概率分布,最后利用测试数据对模型性能进行评估。实验结果表明:评估模型适用于两种多源异构数据,且数据周期越短模型精度越高。

关键词: 全球航班追踪, 多源异构数据, 盲区评估模型, 盲区位置概率分布

Abstract: Aiming at the location report gap of ACARS or ADS-B during global flight tracking, a flight tracking gap assessment model is established based on the ACARS and ADS-B messages. Firstly, the model reconstructs the missing points by cubic spline interpolation algorithm, then divides the point coverage area and the missing area in the evaluation area. SVM algorithm based on Gaussian kernel function is used to obtain the tracking gap location probability distribution inside the missing area. Finally, test data are used to evaluate the model performance. Results show that the assessment model is suitable for two kinds of multi-source heterogeneous data, and the accuracy is higher with shorter data period.

Key words: global flight tracking, multi-source heterogeneous data, tracking gap assessment model, tracking gap location
probability distribution

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