数据与计算发展前沿 ›› 2024, Vol. 6 ›› Issue (3): 139-149.

CSTR: 32002.14.jfdc.CN10-1649/TP.2024.03.015

doi: 10.11871/jfdc.issn.2096-742X.2024.03.015

• 技术与应用 • 上一篇    下一篇

一种面向MR数据定位场景的脏指纹剔除算法

姜楠1(),李易2,*(),李逸静1,牛晓燕1   

  1. 1.中国信息通信研究院，安全研究所，北京 100191
    2.中国科学院计算机网络信息中心，北京 100083
  • 收稿日期:2023-10-22 出版日期:2024-06-20 发布日期:2024-06-21
  • 通讯作者: *李易（E-mail: liyi@cstnet.cn）
  • 作者简介:姜楠，中国信息通信研究院，安全研究所，工程师，长期从事信息通信安全研究，主要研究方向为信息通信安全，大数据计算分析。
    负责论文初稿撰写与仿真模型开发。
    JIANG Nan is an engineer of China Academy of Information and Communication Research, Institute of Security Studies. He has long been engaged in the research of information and communication security. His research interests include information and communication security, and big data analytics.
    In this paper, he is responsible for the paper drafting and simulation model development.
    E-mail: jiangnan@caict.ac.cn|李易，中国科学院计算机网络信息中心，工程师。主要研究方向核心骨干网络运行数据分析，DNS数据分析。
    负责指定论文研究路线及框架，撰写“2背景知识”，对论文进行修改、审定。
    LI Yi is an engineer at the Computer Network Information Center of the Chinese Academy of Sciences. The main research directions are core backbone network operation data analysis and DNS data analysis.
    In this paper, he is responsible for drawing up the paper framework and technological route, writing “2 Background Knowledge”, and paper revision and approval.
    E-mail: liyi@cstnet.cn

An Algorithm of Dirty Fingerprint Rejection for MR Data Localization Scenarios

JIANG Nan1(),LI Yi2,*(),LI Yijing1,NIU Xiaoyan1   

  1. 1. China Academy of Information and Communication Technology, Security Research Institute, Beijing 100191
    2. Computer Network Information Center (CNIC) of the Chinese Academy of Sciences, Beijing 100083
  • Received:2023-10-22 Online:2024-06-20 Published:2024-06-21

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摘要：

【目的】随着通信技术发展与移动设备的普及，MR（测量报告，Measurement Report）数据被广泛应用到无线网络定位中，其中基于MR指纹库匹配的定位方法是精度较高、应用较广泛的方法。然而，位置的计算精度依赖于MR指纹库数据记录的质量，亟需在积累位置指纹库时对数据进行清洗、过滤、位置纠偏等工作，以保证指纹库的数据质量。【方法】因此，本文提出了一种面向MR数据定位场景的脏指纹剔除算法，通过DBSCAN聚类算法识别异常指纹，并纠偏基站位置，建立高质量的指纹数据库，以提升MR数据定位精准性。【结果】本文在农村、市区、郊区3个场景下，分别使用模拟数据进行仿真试验，对本文方法进行分析与评估。【结论】试验结果显示，随着异常指纹剔除及指纹数据库更新，MR数据定位精准度得到有效提升，且所提算法在指纹聚类场景下相比其他算法均存在优势。

关键词: 无线网络定位, MR指纹, 高质量指纹, 指纹库定位

Abstract:

[Objective] With the development of communication technology and the widespread use of mobile devices, Measurement Report (MR) data has been widely applied in wireless network positioning, and the MR fingerprint matching method based on fingerprint database is a widely used and relatively accurate method. However, the computational accuracy of the position depends on the quality of the data records in the MR fingerprint database. There is an urgent need to clean, filter, and position correct the data when accumulating the positional fingerprint database in order to ensure the data quality of the fingerprint database. [Methods] Therefore, this paper proposes a dirty fingerprint rejection algorithm for MR data localization scenarios, which identifies anomalous fingerprints through the DBSCAN clustering algorithm, corrects the location of the base station, and establishes a high-quality fingerprint database in order to improve the accuracy of MR data localization. [Results] In this paper, simulation data are used to conduct simulation experiments in three scenarios: rural, urban, and suburban, and the proposed method is analyzed and evaluated. [Conclusion] The experimental results show that with the removal of abnormal fingerprints and update of the fingerprint database, the accuracy of MR data localization has been effectively improved, and the proposed algorithm has advantages over other algorithms in terms of fingerprint recognition.

Key words: wireless network localization, MR fingerprint, high quality fingerprints, fingerprint database positioning