摘要
随着智能信息社会的不断演进以及智慧城市建设的推进,电子设备的定位准确性和可靠性需求日益突显,特别是在万物互联的背景下,对定位精度和定位质量的要求变得更加迫切。无源定位技术因隐蔽性强、功耗低、不易被感知与干扰等诸多优点被广泛应用于各个领域,尤其近年来,通感一体化(Integrated Sensing and Communication, ISAC)、机器学习、环境反向散射以及智能反射面的引入与发展,为无源定位在6G中的应用提供了新的契机。基于此,阐述了无源定位技术特点及分类;按照参数化的分类方式总结梳理无源定位方法及误差影响因素;讨论了多参数融合无源定位方案与优势;展望了无源定位技术在6G新愿景下典型的应用场景、潜在技术、挑战及未来研究方向。
With the continuous evolution of the smart information society and the advancement of smart city construction,the demand for the accuracy and reliability of electronic device positioning is becoming increasingly prominent.Especially in the context of the Internet of Things,the requirements for positioning accuracy and quality have become more urgent.Passive localization technology,due to its strong concealment,low power consumption,and resistance to perception and interference,is widely applied in various fields.Especially in recent years,the introduction and development of Integrated Sensing and Communication(ISAC),machine learning,ambient backscattering and intelligent reflecting surfaces provide new opportunities for the application of passive positioning in 6G.Based on this,firstly the characteristics and classification of passive positioning technology are elaborated.Secondly,according to the parameterized classification method,the passive positioning method and the influencing factors of error are summarized and sorted out.Furthermore,the advantages of multi-parameter fusion passive localization schemes are discussed.Finally,the typical application scenarios,potential technologies,challenges and future research directions of passive positioning technology under the new vision of 6G are prospected.
作者
李俊霞
王欣
黄高见
徐勇军
郝万明
朱政宇
李兴旺
LI Junxia;WANG Xin;HUANG Gaojian;XU Yongjun;HAO Wanming;ZHU Zhengyu;LI Xingwang(School of Physics and Electronic Information Engineering,Henan Polytechnic University,Jiaozuo 454003,China;School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;School of Electrical and Information Engineering,Zhengzhou University,Zhengzhou 450001,China)
出处
《无线电工程》
2024年第8期1825-1846,共22页
Radio Engineering
基金
河南省重点研发专项(231111210500)
河南省高等学校重点科研项目(23B510001)。
关键词
无源定位
智能反射面
环境反向散射
通感一体化
深度学习
passive positioning
intelligent reflecting surfaces
ambient backscatter
ISAC
deep learning