Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

XIE Jiayi; SUN Huabo; WANG Chun; LU Binbin

doi:10.13203/j.whugis20190120

Volume 46 Issue 8

Aug. 2021

Turn off MathJax

Article Contents

Abstract

References

Geomatics and Information Science of Wuhan University > 2021 > 46(8): 1201-1208. > DOI: 10.13203/j.whugis20190120

XIE Jiayi, SUN Huabo, WANG Chun, LU Binbin. Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale[J]. Geomatics and Information Science of Wuhan University, 2021, 46(8): 1201-1208. DOI: 10.13203/j.whugis20190120

Citation:

PDF (11663 KB)

Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

1.
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
2.
Institute of Aviation Safety, China Academy of Civil Aviation Science and Technology, Beijing 100028, China

Funds:

The National Natural Science Foundation of China U1833201

More Information

Author Bio:
XIE Jiayi, master, specializes in spatial statistics and geographically weighted models.JiayiXie@whu.edu.cn
Corresponding author:
LU Binbin, PhD, associate professor. E-mail: binbinlu@whu.edu.cn
Received Date: November 19, 2019
Published Date: August 04, 2021

Graphical Abstract

Abstract

Abstract

Objectives Unstable approach is one of the most important risks that threatens the flight safety during the descending phase, and is affected by factors such as meteorological and topographical that have strong spatial heterogeneity.
Methods In this article, we use the big data of quick access recorder (QAR) that collected by China Academy of Civil Aviation Science and Technology (CAST) to detect the unstable approach happening in Airbus and Boeing aircrafts in January 2018, and utilize exploratory spatial data analysis methods to explore the spatial patterns and relative influencing factors. In addition, Pearson correlation coefficient and geographically weighted correlation coefficient are used to investigate the pair-wise relationships between unstable approach and factors.
Results Experimental results show that unstable approaches of different aircraft types are distinctive in spatial distributions, and unstable approach of same aircraft type spatially varies in different regions in China. Besides, the correlation description in the fine-grained scale is better than in the global scale.
Conclusions This study provides an important research basis and guidance for the future quantitative cause analysis, which is significant for avoiding such risks.
- unstable approach,
- flight safety,
- spatial heterogeneity,
- space-time cube,
- geographically weighted summary statistics

FullText(HTML)

References (19)

References

[1]	杜红兵, 李珍香. 进近着陆运输飞行事故原因及预防对策研究[J]. 中国安全科学学报, 2006, 16(6): 118-122 doi: 10.3969/j.issn.1003-3033.2006.06.022 Du Hongbing, Li Zhenxiang. Cause Analysis on Approach-and-Landing Loss Accidents and Their Countermeasures[J]. China Safety Science Journal, 2006, 16(6): 118-122 doi: 10.3969/j.issn.1003-3033.2006.06.022
[2]	陈亚青, 孙宏. 进近管制员工作进程分类及工作负荷研究[J]. 中国安全科学学报, 2006, 16(2): 65-68 doi: 10.3969/j.issn.1003-3033.2006.02.013 Chen Yaqing, Sun Hong. Study on Classification of Work Processes and Workload of Approaching Controller[J]. China Safety Science Journal, 2006, 16(2): 65-68 doi: 10.3969/j.issn.1003-3033.2006.02.013
[3]	霍志勤, 罗帆. 近十年中国民航事故及事故征候的统计分析[J]. 中国安全科学学报, 2006, 16(12): 65-71 doi: 10.3969/j.issn.1003-3033.2006.12.013 Huo Zhiqin, Luo Fan. Statistic Analysis on Accidents and Incidents in the Last Decade in China Civil Aviation[J]. China Safety Science Journal, 2006, 16(12): 65-71 doi: 10.3969/j.issn.1003-3033.2006.12.013
[4]	刘方正, 范国磊, 马龙骧. 微下冲气流对飞机着陆性能的影响[J]. 海军航空工程学院学报, 2013(6): 639-642 https://www.cnki.com.cn/Article/CJFDTOTAL-HJHK201306012.htm Liu Fangzheng, Fan Guolei, Ma Longxiang. Influence of Micro-Downburst on Aircraft Landing Performance[J]. Journal of Naval Aeronautical and Astronautical University, 2013(6): 639-642 https://www.cnki.com.cn/Article/CJFDTOTAL-HJHK201306012.htm
[5]	周长春, 胡栋栋. 基于灰色聚类方法的航空公司飞机进近着陆阶段安全性评估[J]. 中国安全生产科学技术, 2012, 8(7): 99-102 https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201207023.htm Zhou Changchun, Hu Dongdong. Safety Assessment of Aircraft During Approach Landing Stage Based on Grey Clustering Method[J]. Journal of Safety Science and Technology, 2012, 8(7): 99-102 https://www.cnki.com.cn/Article/CJFDTOTAL-LDBK201207023.htm
[6]	郭媛媛, 孙有朝, 李龙彪, 等. 民用飞机进近着陆阶段灾难事故类型预测[J]. 航空计算技术, 2016, 16(4): 31-34 doi: 10.3969/j.issn.1671-654X.2016.04.008 Guo Yuanyuan, Sun Youchao, Li Longbiao, et al. Prediction of Catastrophic Accident Types of Civil Aircraft at Approach and Landing Phases[J]. Aeronautical Computing Technique, 2016, 16(4): 31-34 doi: 10.3969/j.issn.1671-654X.2016.04.008
[7]	Hanifa A, Akbar S. Detection of Unstable Approaches in Flight Track with Recurrent Neural Network[C]// International Conference on Information and Communications Technology, Yogyakarta, Indonesia, 2018
[8]	Wang Z, Sherry L, Shortle J F. Feasibility of Using Historical Flight Track Data to Nowcast Unstable Approaches[C]// Integrated Communications Navigation and Surveillance, Herndon, VA, USA, 2016
[9]	王超, 郭九霞, 沈志鹏. 基于基本飞行模型的4D航迹预测方法[J]. 西南交通大学学报, 2009, 44(2): 295-300 doi: 10.3969/j.issn.0258-2724.2009.02.028 Wang Chao, Guo Jiuxia, Shen Zhipeng. Prediction of 4D Trajectory Based on Basic Flight Models[J]. Journal of Southwest Jiaotong University, 2009, 44(2): 295-300 doi: 10.3969/j.issn.0258-2724.2009.02.028
[10]	Wang L, Wu C, Sun R. An Analysis of Flight Quick Access Recorder (QAR) Data and Its Applications in Preventing Landing Incidents[J]. Reliability Engineering and System Safety, 2014, 127: 86-96 doi: 10.1016/j.ress.2014.03.013
[11]	Wang Q, Wu K, Zhang T, et al. Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-Altitude Airport[J]. Chinese Journal of Aeronautics, 2012, 25(3): 361-371 doi: 10.1016/S1000-9361(11)60397-X
[12]	耿宏, 揭俊. 基于QAR数据的飞机巡航段燃油流量回归模型[J]. 航空发动机, 2008, 34(4): 46-50 https://www.cnki.com.cn/Article/CJFDTOTAL-HKFJ200804015.htm Geng Hong, Jie Jun. Fuel Flow Regression Model of Aircraft Cruise Based on QAR Data[J]. Aeroengine, 2008, 34(4): 46-50 https://www.cnki.com.cn/Article/CJFDTOTAL-HKFJ200804015.htm
[13]	Brunsdon C, Fotheringham A S, Charlton M. Geographically Weighted Summary Statistics: A Framework for Localised Exploratory Data Analysis[J]. Computers, Environment and Urban Systems, 2002, 26(6): 501-524 doi: 10.1016/S0198-9715(01)00009-6
[14]	Tobler W R. A Computer Movie Simulating Urban Growth in the Detroit Region[J]. Economic Geography, 1970, 46(2): 234-240 http://www.bioone.org/servlet/linkout?suffix=i1100-9233-18-5-711-b43&dbid=16&doi=10.1658%2F1100-9233(2007)18[711%3AUSOAPI]2.0.CO%3B2&key=10.2307%2F143141
[15]	Gollini I, Lu B, Charlton M, et al. GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models[J]. Journal of Statistical Software, 2014, 63(17), DOI: 10.18637/jss.v063.i17
[16]	Lu B, Harris P, Charlton M, et al. The GWmodel R Package: Further Topics for Exploring Spatial Heterogeneity Using Geographically Weighted Models[J]. Geo-Spatial Information Science, 2014, 17(2): 85-101 http://d.wanfangdata.com.cn/Periodical/dqkjxxkxxb-e201402002
[17]	Brunsdon C, Fotheringham A S, Charlton M E. Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity[J]. Geographical Analysis, 1996, 28(4): 281-298 doi: 10.1111/j.1538-4632.1996.tb00936.x/abstract
[18]	Nakaya T, Fotheringham A S, Brunsdon C, et al. Geographically Weighted Poisson Regression for Disease Association Mapping[J]. Statistics in Medicine, 2005, 24(17): 2 695-2 717 http://injuryprevention.bmj.com/lookup/external-ref?access_num=16118814&link_type=MED&atom=
[19]	Atkinson P M, German S E, Sear D A, et al. Exploring the Relations Between Riverbank Erosion and Geomorphological Controls Using Geographically Weighted Logistic Regression[J]. Geographical Analysis, 2003, 35(1): 58-82 http://www.tandfonline.com/servlet/linkout?suffix=cit0001&dbid=16&doi=10.1080%2F15568318.2017.1422301&key=10.1111%2Fj.1538-4632.2003.tb01101.x

[1]	GUO Wenfei, ZHU Mengmeng, GU Shengfeng, ZUO Hongming, CHEN Jinxin. GNSS Precise Time-Frequency Receiver Clock Steering Model and Parameter Design Method[J]. Geomatics and Information Science of Wuhan University, 2023, 48(7): 1126-1133. DOI: 10.13203/j.whugis20220458
[2]	SUN Leyuan, YANG Jun, GUO Xiye, HUANG Wende. Frequency Performance Evaluation of BeiDou-3 Satellite Atomic Clocks[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20200486
[3]	WU Yiwei, YANG Bin, XIAO Shenghong, WANG Maolei. Atomic Clock Models and Frequency Stability Analyses[J]. Geomatics and Information Science of Wuhan University, 2019, 44(8): 1226-1232. DOI: 10.13203/j.whugis20180058
[4]	AN Xiangdong, CHEN Hua, JIANG Weiping, XIAO Yugang, ZHAO Wen. GLONASS Ambiguity Resolution Method Based on Long Baselines and Experimental Analysis[J]. Geomatics and Information Science of Wuhan University, 2019, 44(5): 690-698. DOI: 10.13203/j.whugis20170091
[5]	LI Mingzhe, ZHANG Shaocheng, HU Youjian, HOU Weizhen. Comparison of GNSS Satellite Clock Stability Based on High Frequency Observations[J]. Geomatics and Information Science of Wuhan University, 2018, 43(10): 1490-1495, 1503. DOI: 10.13203/j.whugis20160537
[6]	WANG Ning, WANG Yupu, LI Linyang, ZHAI Shufeng, LV Zhiping. Stability Analysis of the Space-borne Atomic Clock Frequency for BDS[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1256-1263. DOI: 10.13203/j.whugis20150806
[7]	LIU Zhiqiang, YUE Dongjie, WANG Hu, ZHENG Dehua. An Approach for Real-Time GPS/GLONASS Satellite Clock Estimation with GLONASS Code Inter-Frequency Biases Compensation[J]. Geomatics and Information Science of Wuhan University, 2017, 42(9): 1209-1215. DOI: 10.13203/j.whugis20150542
[8]	HUANG Guanwen, YU Hang, GUO Hairong, ZHANG Juqing, FU Wenju, TIAN Jie. Analysis of the Mid-long Term Characterization for BDS On-orbit Satellite Clocks[J]. Geomatics and Information Science of Wuhan University, 2017, 42(7): 982-988. DOI: 10.13203/j.whugis20140827
[9]	MAO Yue, CHEN Jianpeng, DAI Wei, JIA Xiaolin. Analysis of On-board Atomic Clock Stability Influences[J]. Geomatics and Information Science of Wuhan University, 2011, 36(10): 1182-1186.
[10]	GUO Hairong, YANG Yuanxi. Analyses of Main Error Sources on Time-Domain Frequency Stability for Atomic Clocks of Navigation Satellites[J]. Geomatics and Information Science of Wuhan University, 2009, 34(2): 218-221.

Cited By

Cited by

Periodical cited type(10)

1.	黄观文，曹钰，谭粤，谢威. GNSS星载原子钟在轨性能评估技术进展. 测绘地理信息. 2024(01): 20-28 .
2.	蒋春华，朱美珍，薛慧杰，刘广盛. 基于长短时记忆神经网络的Multi-GNSS卫星钟差建模预报. 大地测量与地球动力学. 2024(03): 257-262 .
3.	艾孝军，孙大伟，贾小林，郭栋，彭腾. GNSS星载原子钟性能评估与噪声分析模型算法研究. 无线电工程. 2023(05): 1041-1051 .
4.	李方能，梁益丰，许江宁，吴苗. BDS/GPS新型铷原子钟长期特性分析. 中国惯性技术学报. 2023(05): 452-461 .
5.	张润哲，刘雪娇，王全喜. 基于方位导引的无人僚机着舰进近引导技术研究. 现代导航. 2023(06): 416-421 .
6.	龚明杰. GPS与GLONASS多频组合伪距单点定位精度分析. 测绘与空间地理信息. 2022(02): 115-117+122 .
7.	樊礼谦，焦文海，蔡洪亮，周巍，徐颖，周舒涵. 北斗三号卫星钟长期稳定性分析. 导航定位学报. 2022(04): 11-19 .
8.	李特，张为成，王建敏，李秀海. 基于不同评价指标的北斗星载原子钟特性分析. 黑龙江工程学院学报. 2022(04): 1-7 .
9.	伏军胜，贾小林，刘家龙，许瑾，贺延伟，张奋. BDS-3卫星与其他GNSS系统卫星原子钟性能分析. 真空与低温. 2022(05): 615-622 .
10.	齐艳丽. 北斗星载原子钟频率稳定度评估. 科技视界. 2022(29): 83-85 .

Other cited types(11)

Get Citation

PDF

XML

Article views (1233) PDF downloads (58) Cited by(21)

Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

Abstract

References

Related Articles

Cited by

Periodical cited type(10)

Other cited types(11)

Catalog

Related

Analysis of Influence Factors for Unstable Approach in Fine⁃Grained Scale

Abstract

References

Related Articles

Cited by

Periodical cited type(10)

Other cited types(11)

Catalog

Related

Export File

Citation

Format

Content