| Citation: | CAO X W，YAO D，SUN F R，et al. Airspace sector planning method based on radar data mining[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（12）：3237-3244 （in Chinese） doi: 10.13700/j.bh.1001-5965.2022.0573
|
With the rapid development of civil aviation, airport airspace has become more crowded. How airspace sector planning methods can be improved has become a key research question. The traditional method has the shortcomings of over-simplified indicators and relying on human experiences. This research offered a novel approach to identify airspace sectors using the trajectory information data mining technique based on raw radar data from ATC. Firstly, effective trajectory data were screened using an autoregressive model. Secondly, a feature point screening model was established to extract the heading, speed, and altitude trajectory feature point set. Through EM clustering, the center of the feature areas was determined, and the regional center of aircraft traffic was identified. The distribution of distinctive regional centers and conflict sites was then used to develop a topological relationship between the centers of the feature area points, and an optimization model based on the spectral clustering technique was created.Finally, the approach control airspace sector scheme is proposed, and simulation results verified the feasibility of the method.
| [1] |
MITCHELL J, SABHNANI G, HOFFMAN R, et al. Dynamic airspace configuration management based on computational geometry techniques: AIAA 2008-7225[R]. Reston: AIAA, 2008.
|
| [2] |
KICINGER R, YOUSEFI A. Heuristic method for 3D airspace partitioning: Genetic algorithm and agent-based approach: AIAA 2009-7058[R]. Reston: AIAA, 2009.
|
| [3] |
LI J, WANG T, HWANG I. A spectral clustering based algorithm for dynamic airspace configuration: AIAA 2009-7056[R]. Reston: AIAA, 2009.
|
| [4] |
亢继方. 空域复杂性因素下的扇区划分研究[D]. 南京: 南京亚洲成人在线一二三四五六区, 2016.
KANG J F. Research on sector division under airspace complexity factors[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2016(in Chinese).
|
| [5] |
毕虹. 基于空域信息的动态扇区划分方法研究[D]. 北京: 北京工业大学, 2013.
BI H. Dynamic airspace sectorization via airspace information[D]. Beijing: Beijing University of Technology, 2013(in Chinese).
|
| [6] |
尹文杰. 空域灵活使用中空域动态规划及流量动态分配技术研究[D]. 天津: 中国民航大学, 2014.
YIN W J. Research on airspace dynamic programming and dynamic allocation of flow technique in the flexible use of airspace[D]. Tianjin: Civil Aviation University of China, 2014(in Chinese).
|
| [7] |
GERDES I, TEMME A, SCHULTZ M. Dynamic airspace sectorisation for flight-centric operations[J]. Transportation Research Part C:Emerging Technologies, 2018, 95: 460-480. doi: 10.1016/j.trc.2018.07.032
|
| [8] |
张文倩, 王瑛, 李超, 等. 飞行流量变化下的动态扇区划分研究[J]. 火力与指挥控制, 2019, 44(1): 125-130. doi: 10.3969/j.issn.1002-0640.2019.01.025
ZHANG W Q, WANG Y, LI C, et al. Research on dynamic sector partitioningunder change of flight flow[J]. Fire Control & Command Control, 2019, 44(1): 125-130(in Chinese). doi: 10.3969/j.issn.1002-0640.2019.01.025
|
| [9] |
REHM F. Clustering of flight tracks[C]//Proceedings of the AIAA Infotech @Aerospace Conference. Reston: AIAA, 2010: 155-164.
|
| [10] |
GARIEL M, SRIVASTAVA A N, FERON E. Trajectory clustering and an application to airspace monitoring[J]. IEEE Transactions on Intelligent Transportation Systems, 2011, 12(4): 1511-1524. doi: 10.1109/TITS.2011.2160628
|
| [11] |
LEIDEN K, ATKINS S. Trajectory clustering for metroplex operations: AIAA 2011-7066[R]. Reston: AIAA, 2011.
|
| [12] |
刘继新, 董欣放, 徐晨, 等. 基于密度峰值的终端区航迹聚类与异常识别[J]. 交通运输工程学报, 2021, 21(5): 214-226.
LIU J X, DONG X F, XU C, et al. Aircraft trajectory clustering in terminal area and anomaly recognition based on density peak[J]. Traffic and Transportation Engineering, 2021, 21(5): 214-226(in Chinese).
|
| [13] |
马天林, 韩壮志. 基于线性预测的雷达航迹压缩算法[J]. 火力与指挥控制, 2019, 44(8): 107-110.
MA T L, HAN Z Z. Research on radar track compression algorithm based on linear prediction[J]. Fire Control & Command Control, 2019, 44(8): 107-110(in Chinese).
|
| [14] |
王莉莉, 彭勃. 基于特征航迹简化模型的中心航迹提取研究[J]. 计算机应用研究, 2019, 36(1): 49-52.
WANG L L, PENG B. Research on central flight track extraction based on simplified track model[J]. Application Research of Computers, 2019, 36(1): 49-52(in Chinese).
|
| [15] |
DONG X F, LIU J X, ZHANG W N, et al. Identifying anomaly aircraft trajectories in terminal areas based on deep auto-encoder and its application in trajectory clustering[J]. Transactions of Nanjing University of Aeronautics and Astronautics, 2020, 37(4): 574-585.
|
| [16] |
郑乐, 隋东, 张军峰, 等. 基于转弯点聚类的航空器飞行轨迹分析[J]. 武汉理工大学学报(交通科学与工程版), 2015, 39(1): 139-143.
ZHENG L, SUI D, ZHANG J F, et al. Analysis of the aircraft flight path based on turning points clustering[J] Journal of Wuhan University of Technology (Transportation Science & Engineering), 2015, 39(1): 139-143(in Chinese).
|
Figures(7) / Tables(7)
Copyright © Journal of Beijing University of Aeronautics and Astronautics
Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@cqjj8.com
Supported by:
Beijing Renhe Information Technology Co., Ltd.
DownLoad:
