基于WebSocket技术无线频谱大数据实时监测系统设计与实现  

Design and Implementation of a Real-time Analysis System for Big Data Wireless Spectrum Monitoring Based on WebSocket

作　　者：高锐 闫光辉[1] 罗浩 严天峰[1,2,3] GAO Rui;YAN Guang-hui;LUO Hao;YAN Tian-feng(School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Gansu ProvincialIndustry Technology Center for Radio Monitoring and Positioning,Lanzhou Jiaotong University,Lanzhou 730070,China;GansuProvincial Engineering Laboratory for High-Precision Beidou Positioning Technology,Lanzhou Jiaotong University,Lanzhou 730070,China;School of Information Science and Engineering of Gansu University of Chinese Medicine,Lanzhou 730000,China)

机构地区：[1]兰州交通大学电子与信息工程学院,兰州730070 [2]兰州交通大学甘肃省无线电监测及定位行业技术中心,兰州730070 [3]兰州交通大学甘肃省高精度北斗定位技术工程实验室,兰州730070 [4]甘肃中医药大学信息工程学院,兰州730000

出　　处：《兰州交通大学学报》2022年第1期52-60,共9页Journal of Lanzhou Jiaotong University

基　　金：国家自然科学基金(62062049,61662066);甘肃省自然科学基金(20JR5RA390);甘肃省青年科技基金(21JR7RA325);教育部人文社会科学研究青年基金(20YJCZH212);甘肃省社科规划青年项目(2021QN027);兰州交通大学青年科学研究基金(2018003)。

摘　　要：伴随着互联网和无线通信技术的快速发展,如何对海量无线监测数据进行处理和干扰源排查成为无线电监管部门面临的困难和挑战之一.针对此问题,提出了一种同相正交信号-功率谱密度转化算法和功率谱密度信号瀑布图可视化方法,以实现对无线信号实时监测的可视化呈现;在此基础上,结合未来无线电监测小型化、网格化的发展趋势,采用HTML5 Canvas,WebSocket和Python Flask技术设计实现了一套切实可行、机动性强、实时性高、支持远程异构网络的无线频谱数据实时监测系统.系统运行结果表明:该系统具有较高的准确性和可信性,可为电磁环境监测提供技术支持,同时为频谱管理人员进行频谱规划和异常信号监测提供决策依据.With the rapid development of Internet and wireless communication technologies,how to deal with massive monitoring data and investigate the interference sources has became one of the major difficulties and challenges.For this reason,an in-phase and quadrature(IQ)signals-power spectral density(PSD)algorithm and its visualization approach are proposed to achieve real-time monitoring of wireless signals.On this basis,considering the development trend of miniaturization and gridding for radio spectrum monitoring in the future,a real-time monitoring system which has many advantages of practicability,portability,strong real-time performance,which can support remote heterogeneous networks,is designed and implemented by using HTML5 Canvas,WebSocket,Python Flask and other computer-related technologies.The results show that this system has high accuracy and credibility,which can provide technical support for electromagnetic environment monitoring,and decision basis for spectrum management personnel in spectrum planning and abnormal signal monitoring.

关 键 词：无线电频谱 功率谱密度 快速傅里叶变换 瀑布图 WebSocket 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]