基于ADS-B的航空器测高系统误差评估方法

金开研; 朱衍波; 许有臣

doi:10.13700/j.bh.1001-5965.2016.0308

基于ADS-B的航空器测高系统误差评估方法

doi: 10.13700/j.bh.1001-5965.2016.0308

金开研^{1, 2, ,},
朱衍波^{1, 2, 3},
许有臣^{1, 2}

1.
民航数据通信有限责任公司研究与发展中心, 北京 100083
2.
国家空管新航行系统技术重点实验室, 北京 10008
3.
北京航空航天大学电子信息学院, 北京 100083

基金项目:

国家自然科学基金 U1433114

民航科技创新引导资金 20150205

详细信息

作者简介:
金开研, 男, 硕士, 工程师。主要研究方向:航空数据分析

朱衍波, 男, 博士, 研究员, 博士生导师。主要研究方向:空中交通管理

通讯作者:
金开研, E-mail:zyb@buaa.edu.cn

中图分类号: V241.4⁺21;O212
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- 被引次数: 0
出版历程
- 收稿日期: 2016-04-18
- 录用日期: 2016-07-16
- 网络出版日期: 2017-04-20

Error evaluation method of aircraft altimetry system based on ADS-B

JIN Kaiyan^{1, 2
, ,},
ZHU Yanbo^{1, 2, 3},
XU Youchen^{1, 2}

1.
R & D Center, Aviation Data Communication Corporation, Beijing 100083, China
2.
National Key Laboratory of CNS/ATM, Beijing 10008
3.
School of Electronic and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

Funds:

National Natural Science Foundation of China U1433114

Scientific and Technological Innovation Guiding Fund of CAAC 20150205

More Information

Corresponding author: Kaiyan, E-mail:zyb@buaa.edu.cn

摘要

摘要:
针对基于广播式自动相关监视（ADS-B）数据的航空器高度保持性能监控中测高系统误差准确评估问题，提出了基于核平滑和混合正态分布模型的数据平滑和拟合分析方法。提出了ADS-B信息低分辨率高度数据的核平滑方法，通过比较分析得到了数据平滑的最优窗宽，基于实测数据的分析证明了该方法对于航空器测高系统误差评价的有效性。针对航空器使用的2套独立的测高学设备具有不同的高度保持性能分布特征的问题，提出了基于混合正态分布模型的拟合分析方法，实测结果表明，该方法可以准确拟合航空器测高系统误差的双峰特征。本文所提出的方法已经在中国RVSM航空器高度保持性能的实际分析中使用，分析结果满足国际民航组织的相关要求。
- 广播式自动相关监视 (ADS-B) /
- 测高系统误差 /
- 核平滑 /
- 混合高斯分布 /
- 模型拟合
Abstract:
Aimed at the accurate evaluation of the altimetry system error for the automatic dependent surveillance-broadcast (ADS-B) height keeping performance monitoring, a data smoothing and fitting analysis method based on the kernel smoothing and mixed-Gaussian distribution was proposed. The kernel smoothing method for improving the resolution of the height data in the ADS-B messages was proposed. The optimal bandwidth of the data smoothing was analyzed. The analysis using real data demonstrates that this error evaluation method of the altimetry system is effective. To solve the problem that the two independent altimetry systems of an aircraft have different height keeping performance distribution characteristics, the fitting method based on the mixed-Gaussian distribution was proposed. The analysis using real data demonstrates that this method can accurately describe the double split peak characteristic of the aircraft altimetry system error. The proposed methods have been used in the analysis of Chinese RVSM aircraft height keeping performance. Evaluation results follow the requirements of International Civil Aviation Organization.
- automatic dependent surveillance-broadcast (ADS-B) /
- altimetry system error /
- kernel smoothing /
- mixed-Gaussian distribution /
- model fitting

HTML全文

图 1 ASE计算的一般步骤

Figure 1. General steps of ASE calculation

下载: 全尺寸图片幻灯片

图 2 不同核函数的比较

Figure 2. Comparison of different kernel functions

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图 3 不同窗宽的比较

Figure 3. Comparison of different bandwidths

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图 4 2种平滑方法的结果比较

Figure 4. Results comparison of two smoothing method

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图 5 航空器ASE的核密度估计

Figure 5. Kernel density estimation of aircraft ASE

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图 6 某航空器基准面与日均值分析

Figure 6. Height reference and daily mean value analysis of an aircraft

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图 7 航空器ASE混合分布拟合

Figure 7. Mixed distribution fitting of aircraft ASE

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图 8 航空器ASE核密度估计的双峰结果

Figure 8. Double peak results for kernel density estimation of aircraft ASE

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图 9 ADS-B航空器高度保持性能地基监控系统界面

Figure 9. Graphical user interface of ground-based ADS-B aircraft height keeping performance monitoring system

下载: 全尺寸图片幻灯片

表 1 个体航空器分布拟合初值

Table 1. Initial values of individual aircraft distribution fitting

参数	拟合初值
α₁	0.5
α₂	0.5
μ₁
μ₂
σ₁
σ₂

下载: 导出CSV

参考文献(15)

[1]	ICAO.Manual on implementation of a 300 m (1000 ft) vertical separation minimum between FL 290 and FL 410 inclusive:Doc 9574-AN/934[S].2nd ed.Montreal:ICAO, 2002:9-12.
[2]	ICAO.Operating procedures and practices for regional monitoring agencies in relation to the use of a 300 m (1000 ft) vertical separation minimum between FL 290 and FL 410 inclusive:Doc 9937-AN/477[S].Montreal:ICAO, 2010:74-76.
[3]	LEBEDEV B.Method of ASE monitoring:ICAO-SASP-WG/WHL/1-WP/07[R].Canberra:ICAO SASP, 2002:2-4.
[4]	LEBEDEV B.Another method of ASE monitoring:ICAO-SASP-WG/WHL/2-WP/10[R].Montreal:ICAO SASP, 2002:1-5.
[5]	ALDIS G, NIXON D.Use of ADS-B for height-keeping monitoring:ICAO-SASP-WG/WHL/12-WP/22[R].Santiago:ICAO SASP, 2007:12-13.
[6]	FAA.Investigation into the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/13-IP/13[R].Montreal:ICAO SASP, 2008:3-4.
[7]	MARTIN L, FALK C.An update to the investigation into the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/14-WP/17[R].Paris:ICAO SASP, 2008:6-12.
[8]	FALK C.An update to the investigation into the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/15-IP/06[R].Montreal:ICAO SASP, 2009:4-5.
[9]	BUTCHER R, FALK C, ALDIS G.Trial-use of the automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/16-WP/24[R].Auckland:ICAO SASP, 2009:8-9.
[10]	FALK C, ALDIS G, BUTCHER R.An update to the investigation into the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/17-WP/21[R].Montreal:ICAO SASP, 2010:19-21.
[11]	FALK C, ALDIS G, BUTCHER R.Progress on the research conducted to determine the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/18-WP/12[R].Brussels:ICAO SASP, 2010:2-5.
[12]	ALDIS G, BARRY S, FALK C, et al.Large-scale study of the use of automatic dependent surveillance-broadcast data for monitoring aircraft altimetry system error:ICAO-SASP-WG/WHL/19-WP/16[R].Montreal:ICAO SASP, 2011:23-26.
[13]	薛留根.现代非参数统计[M].北京:科学出版社, 2015:173. XUE L G.Modern nonparametric statistics[M].Beijing:Science Press, 2015:173(in Chinese).
[14]	JEFFREY S S.Smoothing methods in statistics[M].Berlin:Springer, 1996:54-55.
[15]	BOWMAN A W, AZZALINI A.Applied smoothing techniques for data analysis[M].New York:Oxford University Press, 1997:31.