利用机器学习的GNSS欺骗检测综述  

Overview of GNSS Spoofing Detection Using Machine Learning

作　　者：周雅兰 宋晓鸥[1] ZHOU Yalan;SONG Xiao’ou(School of Information Engineering,Engineering University of PAP,Xi’an 710086,China)

机构地区：[1]武警工程大学信息工程学院,西安710086

出　　处：《计算机工程与应用》2024年第17期62-73,共12页Computer Engineering and Applications

基　　金：国家自然科学基金(61801516)。

摘　　要：近年来,随着全球卫星导航的重要性日益突出,欺骗检测成为热点研究问题。机器学习作为一种低成本的方法,具有自动从复杂数据中学习规律的能力,并且已在物联网欺骗检测中取得较好的效果,因此越来越多的研究将其用于GNSS欺骗干扰检测。从基于机器学习进行GNSS欺骗检测的基本流程出发,阐述了利用机器学习进行GNSS检测的数据采集和预处理。根据机器学习在欺骗检测中发挥的作用,将基于机器学习的GNSS欺骗检测分为基于信号分类以及基于信息验证的机器学习GNSS欺骗干扰检测两大类进行归纳与总结。最后,根据现有研究问题提出了对未来发展方向的展望。In recent years,with the increasing importance of global satellite navigation,deception detection has become a hot research issue.As a low-cost method,machine learning has the ability to automatically learn rules from complex data,and has achieved good results in the Internet of things spoofing detection.Therefore,more and more studies have used it for GNSS spoofing detection.Firstly,starting from the basic process of GNSS spoofing detection based on machine learning,the data acquisition and preprocessing of GNSS detection using machine learning are described.Then,according to the role of machine learning in spoofing detection,GNSS spoofing detection based on machine learning is divided into two categories:GNSS spoofing detection based on signal classification and GNSS spoofing detection based on information verification.Finally,according to the existing research problems,the prospect of future development direction is put forward.

关 键 词：机器学习 神经网络 全球卫星导航系统(GNSS) 欺骗检测 欺骗干扰 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]