地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (4): 560-569.doi: 10.12082/dqxxkx.2019.180395

• 论文 • 上一篇    下一篇

基于大数据的无人机云交换平台统计分析技术研究

柏艺琴1(), 陈新锋1, 原军锋2   

  1. 1.中国民航科学技术研究院,北京 100028
    2.北京享飞网络科技有限公司,北京 100016
  • 收稿日期:2018-08-24 修回日期:2019-01-06 出版日期:2019-04-24 发布日期:2019-04-24
  • 作者简介:

    作者简介:柏艺琴(1979-),女,湖南长沙人,硕士,主要从事无人机运行数据分析和无人机运行管理研究。 E-mail:baiyq@mail.castc.org.cn

  • 基金资助:
    国家重点研发计划项目(2017YFB0503005)

Statistical Analysis Technology of UAS Cloud Data Exchange Platform based on Big Data

Yiqin BAI1,*(), Xinfeng CHEN1, Junfeng YUAN2   

  1. 1. China Academy of Civil Aviation Science and Technology, Beijing 100028, China
    2. Beijing Xiangfei Network Technology Company Limited, Beijing 100016, China
  • Received:2018-08-24 Revised:2019-01-06 Online:2019-04-24 Published:2019-04-24
  • Contact: Yiqin BAI E-mail:baiyq@mail.castc.org.cn
  • Supported by:
    National Key Research and Development Program of China, No.2017YFB0503005

摘要:

随着无人机在各行业应用的迅速普及和大规模应用,民航局监管的无人机数量和无人机运行数据呈现海量增长,在给政府和行业监管带来便利的同时,也给传统的数据分析方法带来了极大的挑战。本文阐述了民航局无人机云交换平台的运行大数据的现状,分析了传统无人机运行数据统计分析存在的技术瓶颈,提出了基于大数据进行无人机运行数据统计分析方法,建立了无人机云数据交换平台大数据统计和分析系统的设计框架,并概述了如何基于Apache Spark和Cassandra数据库的大数据分析方法将无人机云交换平台生产的海量数据快速处理、存储、统计和分析的研究思路和方法,以及实现各类无人机运行特征分析的情况。目前基于本文的研究成果不仅可以满足行业主管部门对无人机运行数据统计的需求,还对掌握和了解中国无人机运行特征,探索更合适的无人机管理措施和健全无人机监管体制机制,有非常重要的意义。

关键词: 大数据分析, 大数据架构, 无人机云数据, 无人机运行分析, 中国民用航空局

Abstract:

After several years of development, light and small unmanned aircraft systems (UASs) have been widely used in various industries both in China and many other countries. However, the UASs have many models, with scattered equipments and no systematic management. Meanwhile, some safety issues exist. This urgently requires the relevant regulatory authorities to regulate, supervise, and maintain safe flight operations by taking their operating rules and characteristics into account. In order to standardize the operation of light and small civil UASs across the country and promote the industry development, the Civil Aviation Administration of China has issued the "Provisions for the Operation of Light and Small Unmanned Aircraft (for Trial Implementation)" advisory circular and the "Specification for Interface Data of Unmanned Aircraft System Cloud System". The UAS cloud data exchange platform was developed in 2016, and the data sharing of multiple UAS cloud systems in China was realized. With this platform the UASs registered in different UAS cloud systems are visible to each other in the same airspace, which improved the flight safety of China's low-altitude airspace. However, with the rapid development of the application of the unmanned aerial vehicle (UAV) industry, the number of UAVs supervised by the Civil Aviation Authority and the data on the operation of the UAVs has increased dramatically, which has also brought great challenges to the traditional data management methods. In this paper, we will describe the current situation of the operation of big data from the UAS cloud data exchange platform in China followed by discussion on the technical bottle necks in the statistical analysis of the operation data of the traditional UAS. Then we will propose a statistical analysis method for the UAS operation data, and establish a framework of statistical analysis of big data from the cloud data exchange platform. In the end, we will outline how to use Apache Spark and Cassandra database to quickly process, store, count, and analyze the massive data generated by the UAS cloud data exchange platform. The research situation of implementing various statistical index algorithms based on the platform is introduced in detail. This research not only improves the efficiency of statistical analysis of UAS operation data, but also provides the operation management rules of China's light and small UASs from multiple dimensions. sWe highlight that the UAS has significant operational characteristics, which are different from general and transportation aviations. This paper provides reference for government and industry decision-making, which has strong practical significance.

Key words: big data analysis, big data architecture, UAS cloud data exchange, UAS operation analysis, Civil Aviation Administration of China