中国民航大学学报

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基于核密度估计的飞行高度层识别

谢春生,李少华   

  1. (中国民航大学空管学院,天津300300)
  • 收稿日期:2017-05-20 修回日期:2017-06-27 出版日期:2018-08-25 发布日期:2018-10-25
  • 作者简介:谢春生(1975—),男,吉林榆树人,副教授,硕士,研究方向为空域规划与飞行程序设计、飞机性能分析.
  • 基金资助:
    国家自然科学基金项目(61603396,U1333116)

Flight level identification based on kernel density estimation

XIE Chunsheng, LI Shaohua   

  1. (College of Air Traffic Management, CAUC, Tianjin 300300, China)
  • Received:2017-05-20 Revised:2017-06-27 Online:2018-08-25 Published:2018-10-25

摘要: 随着碳交易市场的开放,同时兼顾安全运行品质提高和节能减排技术开发成为航空公司运营的焦点问题,而优化飞行高度层是一种有效措施。因此,提出一种从实际运行获取的大量飞行轨迹中识别出最优飞行高度层的方法。分析飞机飞行轨迹的空间特征,建立飞行轨迹间基于Hausdorff 距离的差异度矩阵模型。采用核密度估计方法实现盛行飞行轨迹识别,根据盛行飞行轨迹与飞行高度层关系,提出一种精细化高度层定义方法。最后,以某公司ZGNN-ZSNJ 航班为例,有效识别航班运行的最优高度层,同时验证该方法的安全经济性。

关键词: 空中交通流, 飞行高度层, 核密度估计, 节能减排

Abstract: With the opening of carbon trading market, safety operation and development of energy-saving emission reduction technology have become focuses of airline operation. A method of identifying the optimal flight level basing on flight data from airlines is presented. By analyzing the spatial characteristics of flight trajectory, difference matrix model basing on Hausdorff distance is established. The kernel density estimation method is used to degree identify prevalent flight trajectory. According to the relationship between flight path and flight level, a refined method of flight level identification is proposed. Finally, taking ZGNN-ZSNJ flight data of an airline as example,the optimal flight level can be effectively distingnished; meanwhile, the safety and economy of the current method is verified.

Key words: air traffic flow, flight level, kernel density estimation, energy-saving and emission-reduction

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