Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream

Zhuxi ZHANG; Wang TIAN; Shaochuan ZHU; Hongyan LIU; Xi ZHU

doi:10.11959/j.issn.2096-3750.2020.00181

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Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream

Topic:IoT in Intelligent Transportation | 更新时间：2024-06-05

- Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream
- Chinese Journal on Internet of Things Vol. 4, Issue 3, Pages: 60-68(2020)
- 作者机构：
  
  1. 北京航空航天大学综合交通大数据应用技术国家工程实验室，北京 100083
  2. 中国人民解放军32751单位，北京 100039
  3. 北京航空航天大学大型飞机高级人才培训班，北京 100083
  4. 北京航空航天大学电子信息工程学院，北京 100083
  4. 北京航空航天大学前沿科学技术创新研究院，北京 100083
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-3750.2020.00181
  CLC： V355.1
- Published：30 September 2020，
  
  Published Online：2020-09，
- 稿件说明：
移动端阅览
ZHUXI ZHANG, WANG TIAN, SHAOCHUAN ZHU, et al. Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream. [J]. Chinese journal on internet of things, 2020, 4(3): 60-68.
DOI：

ZHUXI ZHANG, WANG TIAN, SHAOCHUAN ZHU, et al. Research on real-time fusion method of multi-source heterogeneous flight trajectory data stream. [J]. Chinese journal on internet of things, 2020, 4(3): 60-68. DOI： 10.11959/j.issn.2096-3750.2020.00181.

摘要

二次雷达和广播式自动相关监视（ADS-B

automatic dependent surveillance-broadcast）是在空域监视系统中共存的两种主要监视手段，为了提高监视的精度和稳定性，实现二次雷达和 ADS-B 航迹实时融合至关重要。针对现有方法难以满足大规模航迹的实时融合需求，设计了一种使用大数据技术的二次雷达与 ADS-B 数据流实时融合的方法。该方法基于微批处理的大数据处理框架，遵循MapReduce编程模型，在得到较高质量融合航迹的同时，保障了系统数据处理的高并发能力与实时性。最后，基于真实航班数据开展了航迹实时融合仿真实验，验证了方法的可行性。

Abstract

Secondary surveillance radar (SSR) and automatic dependent surveillance-broadcast (ADS-B) are the two main surveillance methods coexisting in the airspace surveillance system.In order to improve the accuracy and stability of surveillance

real-time fusion of SSR and ADS-B trajectory is crucial.In view of the fact that the existing methods are difficult to meet the real-time fusion requirements of large-scale trajectories

a real-time fusion method of SSR and ADS-B data streams was designed with big data technology.This method was based on the big data processing framework of micro-batch processing and followed the MapReduce programming model.While obtaining a fusion trajectory of high quality

it ensured high concurrency and real-time data processing capability of the system.Finally

a real-time flight simulation experiment based on real flight data was carried out to verify the feasibility of the method.

关键词

航迹融合多源异构微批处理MapReduce流式大数据

Keywords

trajectory fusionmulti-source heterogeneousmicro-batch processingMapReducestreaming big data

references

中国民用航空局.2018年民航行业发展统计公报[R]. 2019.

CAAC.Civil aviation industry development statistical bulletin 2018[R]. 2019.

前瞻产业研究院.2019年全年中国民航业市场分析：运输飞机数量接近4 000架,营业收入突破万亿元[R]. 2020.

Forward Business Information Co.,Ltd.,Shenzhen. Market analysis of China civil aviation industry for 2019:the number of transport aircrafts is close to 4 000,operating revenue exceeds trillion yuan[R]. 2020.

王冶 . 空中交通管理自动化系统的设计与实现[D]. 厦门:厦门大学, 2015.

WANG Y . Design and implementation of air traffic management automation system[D]. Xiamen:Xiamen University, 2015.

王洪, 刘昌忠, 汪学刚 . 二次雷达 S 模式综述[J]. 电讯技术, 2008,48(7): 113-118.

WANG H, LIU C Z, WANG X G . Mode S for secondary surveillance radar (SSR):an introduction and overview[J]. Telecommunication Engineering, 2008,48(7): 113-118.

ZHANG J, LIU W, ZHU Y B . Study of ADS-B data evaluation[J]. Chinese Journal of Aeronautics, 2011,24(4): 461-466.

孙沂, 吴仁彪 . 空管自动化系统的多雷达与 ADS-B 数据融合技术综述[C]// 第二十五届中国（天津）2011’IT、网络、信息技术、电子、仪器仪表创新学术会议. 2011: 19-23.

SUN Y, WU R B . The data fusion of multi-radar and ADS-B in ATCautomation system[C]// The 25th China (Tianjin) 2011’IT,Network,Information Technology,Electronics,Instrumentation Innovation Conference. 2011: 19-23.

张军 . 空域监视技术的新进展及应用[J]. 航空学报, 2011,32(1): 1-14.

ZHANG J . New development and application of airspace surveillance technology[J]. Acta Aeronautica et Astronautica Sinica, 2011,32(1): 1-14.

BAUD O, HONORE N, TAUPIN O . Radar/ADS-B data fusion architecture for experimentation purpose[C]// 2006 9th International Conference on Information Fusion. IEEE, 2006: 1-6.

白松浩 . 多雷达与 ADS 数据融合的可变周期更新算法[J]. 交通运输工程学报, 2007,7(2): 19-23.

BAI S H . Variable period updating algorithm of multiradar and ADS data fusion[J]. Journal of Traffic and Transportation Engineering, 2007,7(2): 19-23.

刘伟, 黄智刚, 张军 ,等. 星基 ADS 与雷达误差校准算法的研究[J]. 航空学报, 2006,27(1): 120-124.

LIU W, HUANG Z G, ZHANG J ,et al. Studies on satellite-based ADS and radar registration algorithm[J]. Acta Aeronautica et Astronautica Sinica, 2006,27(1): 120-124.

周雷, 辛晓娜, 陈川波 . 结合 ADS-B 的航管监视数据融合关键技术[J]. 计算机工程与应用, 2013,49(14): 231-235.

ZHOU L, XIN X N, CHEN C B . Key techniques of ATC surveillance data fusion with ADS-B[J]. Computer Engineering and Applications, 2013,49(14): 231-235.

董宇涵, 山秀明, 任勇 . 一种高性能航迹融合反馈系统的设计与实现[J]. 微计算机信息, 2005,21(12S): 145-147.

DONG Y H, SHAN X M, REN Y . A high performance track fusion system with feedback[J]. Microcomputer Information, 2005,21(12S): 145-147.

翟羽佳 . 多雷达信号与 ADS-B 数据融合技术浅析[J]. 空中交通, 2017:27.

ZHAI Y J . A brief discussion on data fusion technology of multi-radar signal and ADS-B signal[J]. Air Traffic, 2017:27.

许文君 . 空管自动化系统及数据融合方法研究[D]. 南京:南京邮电大学, 2020.

XU W J . Research on air traffic control automation system and data fusion method[D]. Nanjing:Nanjing University of Posts and Telecommunication, 2020.

张杰, 王丽娜, 赵媛 ,等. 基于 ZeroMQ 消息通讯的多源空中目标跟踪处理平台设计[J]. 计算机测量与控制, 2018,26(9): 219-222.

ZHANG J, WANG L N, ZHAO Y ,et al. Design of multi-source tracking platform for air target based on ZeroMQ communication library[J]. Computer Measurement ＆ Control, 2018,26(9): 219-222.

李小智, 陶勇 . 基于消息中间件的航班信息显示系统的设计与实现[J]. 计算机系统应用, 2010,19(10): 7-11.

LI X Z, TAO Y . Design and implementation of flight information display system based on message-oriented middleware[J]. ComputerSystems ＆ Applications, 2010,19(10): 7-11.

李文逍, 杨小虎 . 基于分布式缓存的消息中间件存储模型[J]. 计算机工程, 2010,36(13): 93-95.

LI W X, YANG X H . Storage model based on distributed cache for message oriented middleware[J]. Computer Engineering, 2010,36(13): 93-95.

JOHN V, LIU X . A survey of distributed message broker queues[J]. arXiv:1704.00411, 2017

陈纯 . 流式大数据实时处理技术、平台及应用[J]. 大数据, 2017,3(4): 1-8.

CHEN C . Real-time processing technology,platform and application of streaming big data[J]. Big Data Research, 2017,3(4): 1-8.

CAI Y J, WU B, ZHANG X W ,et al. Flow identification and characteristics mining from Internet traffic with Hadoop[C]// 2014 International Conference on Computer,Information and Telecommunication Systems (CITS). IEEE, 2014: 1-5.

VAIDYA M, DESHPANDE S . Study of Hadoop-based traffic management system[J]. IJCA Proceedings of ICRTITCS, 2013,3: 38-42.

SAFAEI A A . Real-time processing of streaming big data[J]. Real-Time Systems, 2017,53(1): 1-44.

SHAHRIVARI S . Beyond batch processing:towards real-time and streaming big data[J]. Computers, 2014,3(4): 117-129.

DEAN J, GHEMAWAT S . MapReduce:simplified data processing on large clusters[J]. Communications of the ACM, 2008,51(1): 107-113.

DEAN J, GHEMAWAT S . MapReduce[J]. Communications of the ACM, 2008,51(1): 107-113.

李建江, 崔健, 王聃 ,等. MapReduce 并行编程模型研究综述[J]. 电子学报, 2011,39(11): 2635-2642.

LI J J, CUI J, WANG D ,et al. Survey of MapReduce parallel programming model[J]. Acta Electronica Sinica, 2011,39(11): 2635-2642.

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