基于电磁环境数据的信息挖掘与关联分析
作者:
作者单位:

1.哈尔滨工程大学 信息与通信工程学院,黑龙江 哈尔滨 150000;2.装备发展部驻济南地区军事代表室,山东 济南 250100;3.中国电波传播研究所,山东 青岛 266107

作者简介:

李爽(1997-),女,黑龙江省绥化市人,在读硕士研究生,主要研究方向为电磁数据分析挖掘、知识图谱.email:shuang97@hrbeu.edu.cn.
刘海鹏(1981-),男,济南市人,主要研究方向为通信工程.
郭兰图(1982-),男,山东省青岛市人,硕士,主要研究方向为频谱管理、复杂电磁环境建模等.

通讯作者:

*郭兰图 email:guolantu@163.com

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伦理声明:



Information mining and association analysis based on electromagnetic environment data
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Affiliation:

1.School of Information and Communication Engineering, Harbin Engineering University, Harbin Heilongjiang 150000, China;2.Military Representative Office of Equipment Development Department in Jinan Area, Jinan Shandong 250100, China;3.China Research Institute of Radio Wave Propagation, Qingdao Shandong 266107, China

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    摘要:

    城市通信技术的改革换代和用频设备的逐渐增多使得电磁环境变得越来越复杂。充分了解频谱资源利用的特性是提高频谱管理效率的关键。为了更全面地探索频谱利用的特点,提出一套完整的对复杂多样电磁环境大数据进行详细数据质量分析和处理的流程,分别对处于同一服务的不同信道、处于不同服务的不同信道进行频谱相关性分析,证明了频谱之间的相关性;对电磁环境大数据进行属性构造,构造了频率维占用度和时间维占用度属性。引入图像处理领域的多维混合高斯模型,对电磁信号进行背景噪声的去除,提取电磁信号,为后续的信息挖掘和关联分析奠定基础。

    Abstract:

    With the development of urban communication technology and the increase of frequency equipment, the electromagnetic environment becomes more and more complex. Fully understanding the characteristics of spectrum resource utilization in the past is the key to improve the efficiency of spectrum management. A complete process about detailed data quality analysis for big data in complex and diverse electromagnetic environment is proposed, in order to explore the characteristics of spectrum utilization more comprehensively. The spectrum correlation for different channels in the same service, and for different channels in different services, is performed. Attribute construction is carried out for big data of electromagnetic environment, including the attributes of frequency dimension occupancy and time dimension occupancy. The multi-dimensional Gaussian mixture model in the field of image processing is introduced to remove the background noise of the electromagnetic signal and extract the electromagnetic signal, which can lay the foundation for the subsequent information mining and association analysis.

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李爽,刘海鹏,郭兰图.基于电磁环境数据的信息挖掘与关联分析[J].太赫兹科学与电子信息学报,2022,20(1):8~15

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  • 收稿日期:2021-04-21
  • 最后修改日期:2021-05-01
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  • 在线发布日期: 2022-02-23
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