摘要
本文设计了基于大数据分析的通信信号智能检测系统。基础设施层在VM虚拟机上创建多个Xen虚拟机,通过数据持久化设计实现信息虚拟化存储与管理,并将采集的数据通过网络通信层传输至核心服务层,核心服务层采用大数据分析方法构建通信信号检测模型,通过捕捉相邻信号之间非线性时空动作,评价相邻行为之间工作状态的关联性,预测信号行为后续工作状态,实现通信信号检测,并将识别结果反馈给用户接口层实时查看。实验结果显示,该系统的通信信号检测正确率始终高于95%,识别结果准确、可靠;异常信号检测的漏拒率较低,且识别效率高,具有全面、高效的特征。
In the paper,an intelligent detection system of communication signals based on big data analysis is designed.The infrastructure layer creates multiple Xen virtual machines on the VM virtual machine,realizes information virtualization storage and management through data persistence design,and transmits the collected data to the core service layer through the network communication layer.The core service layer uses the big data analysis method to build the communication signal identification model.It evaluates the relevance of the working state between adjacent behaviors,predicts the subsequent working state of signal behaviors,realizes the communication signal recognition,and feeds back the recognition results to the user interface layer for real-time viewing.The experiment results show that the recognition accuracy of the system is always higher than 95%,and the recognition result is accurate and reliable.The detection rate of intrusion signal is low,and the detection efficiency is high.
作者
林统喜
钟福龙
Lin Tongxi;Zhong Fulong(Information Engineering,Guangzhou Huashang Vocational College,Guangzhou 511300,China)
出处
《单片机与嵌入式系统应用》
2021年第12期35-38,共4页
Microcontrollers & Embedded Systems
基金
广东省普通高校特色创新项目(2019GKQNCX088)。
关键词
通信信号
智能检测系统
特征向量
大数据分析
optical communication signal
intelligent detection system
feature vector
big data analysis
作者简介
通信作者:林统喜(讲师),主要研究方向为计算机应用技术。jiiiop794@126.com;钟福龙(讲师),主要研究方向为计算机应用技术。
