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基于PHMM的终端区航空器综合态势识别
引用本文:赵元棣,孙禾,王洁宁,李波.基于PHMM的终端区航空器综合态势识别[J].中国科技论文在线,2013(10):1068-1072.
作者姓名:赵元棣  孙禾  王洁宁  李波
作者单位:[1]中国民航大学天津市空管运行规划与安全技术重点实验室,天津300300 [2]中国民航大学空中交通管理研究基地,天津300300 [3]南昌航空大学数学与信息科学学院,南昌330063
基金项目:国家自然科学基金资助项目(61039001);中央高校基本科研业务费专项资金资助项目(ZXH2012N004ZXH20120002);中国民航大学科研启动资金资助项目(2012QD02X)
摘    要:航空器在终端区飞行时,由于受到诸多因素的影响,导致其不能严格按照计划航线飞行。通过分析历史航迹数据,提出了一种基于并行隐马可夫模型的终端区航空器综合态势识别方法。首先提取航迹数据的各类特征点,然后根据其x坐标、Y坐标以及Z坐标建立3个隐马尔可夫模型。通过训练3个模型的参数,对航空器在终端区内的高度态势、速度态势以及方向态势进行识别。最后采用综合分析方法对航空器的综合态势进行识别。实验表明,该方法能够快速、准确、有效地识别出终端区航空器的综合飞行态势,为管制员发布管制指令提供依据。

关 键 词:模式识别  空中交通管理  并行隐马尔可夫模型  综合态势识别  终端区

Comprehensive situation identification of terminal area aircraft based on PHMM
Zhao Yuandi,Sun He,Wang Jiening,Li Bo.Comprehensive situation identification of terminal area aircraft based on PHMM[J].Sciencepaper Online,2013(10):1068-1072.
Authors:Zhao Yuandi  Sun He  Wang Jiening  Li Bo
Institution:1. Tianjin Air Traffic Management Operational Planning and Safety Technology Laboratory ,Civil Aviation University of China, Tianjin 300300, China; 2. Air Traffic Management Research Base, Civil Aviation University of China, Tianjin 300300, China ; 3. College of Mathematics and Information Science, Nanchang Hangkong University, Nanchang 330063 ; China)
Abstract:When the aircraft fly in the terminal area, they will not follow the planned routes strictly due to many influencing factors. Through analyzing the historical traiectory data, a comprehensive situation identification method of terminal area aircraft based on Parallel Hidden Markov Model (PHMM) is proposed. Firstly, different kinds of feature points of trajectory data are ex- tracted. Then three PHMMs are established according to the x-, y- and z-coordinates. On this basis, the height, velocity and di- rection situations of the aircraft in the terminal area are identified prehensive situation of aircraft is identified through an integrated method can identify the comprehensive flight situation of terminal the basis for controllers to give instructions. by training parameters of these three models. Finally, the comanalysis. The experiment results demonstrate that the proposed area aircraft quickly, accurately and efficiently, and can provide
Keywords:pattern recognition  air traffic management  Parallel Hidden Markov Model  comprehensive situation identification  terminal area
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