北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (2): 116-123.doi: 10.13190/j.jbupt.2020-191

• 车联网专题 • 上一篇    下一篇

多径信号辅助的网联车辆无线协作定位

初星河, 路兆铭, 王鲁晗, 武穆清, 温向明   

  1. 1. 北京邮电大学 信息与通信工程学院, 北京 100876;
    2. 北京邮电大学 先进信息网络北京实验室, 北京 100876
  • 收稿日期:2020-10-03 出版日期:2021-04-28 发布日期:2021-04-28
  • 通讯作者: 路兆铭(1986-),男,副教授,E-mail:lzy0372@bupt.edu.cn. E-mail:lzy0372@bupt.edu.cn
  • 作者简介:初星河(1996-),男,博士生.
  • 基金资助:
    国家自然科学基金项目(61801047)

Multi-Path Assisted Cooperative Radio-Based Localization for Connected Vehicles

CHU Xing-he, LU Zhao-ming, WANG Lu-han, WU Mu-qing, WEN Xiang-ming   

  1. 1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. Beijing Laboratory of Advanced Information Networks, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2020-10-03 Online:2021-04-28 Published:2021-04-28

摘要: 为解决全球定位系统(GPS)和北斗卫星导航系统(BDS)等传统定位方式在信号被遮挡的区域定位范围受限以及精度不足的问题,基于第5代移动通信系统和车联网技术提出了一种多径信号辅助的网联车辆无线协作定位方法.首先将车联网中接收端与发射端之间多径信号成分携带的定位信息提取成多径定位线段,并基于最小二乘法估计出接收端与发射端之间的相对位置;然后基于置信传播算法,将相对位置信息以及部分覆盖的GPS/BDS信息进行协作融合,得出整个车联网中各个车辆的位置.仿真结果表明,在不同的车辆密度和GPS/BDS可用概率下,新算法能提升网联车辆的定位精度,有效解决车辆GPS/BDS覆盖不充分的问题,为网联车辆提供高精度的定位.

关键词: 网联车辆, 多径信号, 信号定位, 置信传播, 协作定位

Abstract: In order to solve the less-accuracy and insufficient-coverage problem of the traditional localization methods like global positioning system (GPS) and BeiDou navigation satellite system (BDS) in the areas where the signals are blocked, a multi-path assisted cooperative radio-based localization method is proposed for connected vehicles based on the fifth generation of mobile communications system and vehicle to everything. In detail, the localization information carried by multi-path components from the transmitter to the receiver in vehicle network is modeled into multi-path positioning segments, thus their relative position is calculated based on least squared algorithm. Then a belief propagation based algorithm is presented to calculate the position of each vehicle by fusing the relative positioning information and the partial covered GPS/BDS information. Simulations show that the algorithm can improve the localization accuracy over different vehicle densities and different GPS/BDS available probabilities, which further indicates that the algorithm can solve the GPS/BDS insufficient-coverage problem so as to provide high-accuracy localization for connected vehicles.

Key words: connected vehicle, multi-path, radio-localization, belief propagation, cooperative localization

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