非视距条件下基于特征融合的UWB到达角估计方法

曾文敏; 郑柏烽; 刘晋廷; 鲍亚川; 尹继凯; 李建佳; 张霆廷

doi:10.11959/j.issn.2096-3750.2025.00495

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非视距条件下基于特征融合的UWB到达角估计方法

理论与技术 | 更新时间：2026-01-04

- 非视距条件下基于特征融合的UWB到达角估计方法
- Feature fusion method for UWB angle of arrival estimation under non-line-of-sight conditions
- 物联网学报 2025年9卷第4期页码：51-61
- 作者机构：
  
  1.哈尔滨工业大学（深圳）空天网络与智能感知重点实验室，广东深圳 518000
  2.香港科技大学（广州）物联网学域，广东广州 511453
  3.中国电子科技集团公司第五十四研究所综合时空网络与装备技术全国重点实验室，河北石家庄 050081
  4.中国电子科技集团公司第五十四研究所，河北石家庄 050081
- 作者简介：
  
  [ "曾文敏（2001‒ ），女，哈尔滨工业大学（深圳）硕士生，主要研究方向为超宽带定位。" ]
  [ "郑柏烽（2003‒ ），男，哈尔滨工业大学（深圳）在读，主要研究方向为超宽带定位、多传感器融合定位。" ]
  [ "刘晋廷（1999‒ ），男，香港科技大学（广州）硕士生，主要研究方向为无线传感器网络。" ]
  [ "鲍亚川（1985‒ ），男，博士，中国电子科技集团公司第五十四研究所研究员，主要研究方向为卫星导航、室内地下导航。" ]
  [ "尹继凯（1972‒ ），男，硕士，中国电子科技集团公司第五十四研究所研究员，主要研究方向为卫星导航。" ]
  [ "李建佳（1997‒ ），男，中国电子科技集团公司第五十四研究所综合时空网络与装备技术全国重点实验室博士生，研究方向为阵列式高精度测角定位技术。" ]
  [ "张霆廷（1980‒ ），男，哈尔滨工业大学（深圳）教授、博士生导师，信息科学与技术学院院长，主要研究方向为无线定位理论、脉冲超宽带技术、通信感知一体化、车联网。" ]
- 基金信息：
  
  国家自然科学基金面上项目(62171160);广东省重点实验室项目（2024）(2024KSYS023);深圳市重点实验室项目(ZDSYS20210623091808025);鹏城实验室重大重点项目(PCL2024A01);卫星导航系统与装备技术国家重点实验室开放基金资助项目(CEPNT2022A03);中国电子科技集团公司第五十四研究所技术开发（委托）项目(HX20210106)
- DOI：10.11959/j.issn.2096-3750.2025.00495
  中图分类号：
- 收稿：2025-03-05，
  
  修回：2025-06-10，
  
  纸质出版：2025-12-10
- 稿件说明：
移动端阅览
曾文敏,郑柏烽,刘晋廷等.非视距条件下基于特征融合的UWB到达角估计方法[J].物联网学报,2025,09(04):51-61.

ZENG Wenmin,ZHENG Bofeng,LIU Jinting,et al.Feature fusion method for UWB angle of arrival estimation under non-line-of-sight conditions[J].Chinese Journal on Internet of Things,2025,09(04):51-61.
曾文敏,郑柏烽,刘晋廷等.非视距条件下基于特征融合的UWB到达角估计方法[J].物联网学报,2025,09(04):51-61. DOI： 10.11959/j.issn.2096-3750.2025.00495.

ZENG Wenmin,ZHENG Bofeng,LIU Jinting,et al.Feature fusion method for UWB angle of arrival estimation under non-line-of-sight conditions[J].Chinese Journal on Internet of Things,2025,09(04):51-61. DOI： 10.11959/j.issn.2096-3750.2025.00495.

摘要

超宽带（UWB

ultra-wideband）技术能够提供高精度的定位信息，在室内定位中具有显著优势。到达角（AOA

angle of arrival）估计作为UWB定位的关键技术之一，对提高定位精度至关重要。然而，在实际应用中，UWB AOA估计面临着诸多挑战，尤其是在非视距（NLOS

non-line-of-sight）、天线硬件损伤、环境变化情况等复杂情况下，这些因素会造成信号失真和测量偏差，从而降低估计的精度，而传统的建模方法往往难以有效处理这些非线性问题。因此，设计了一种基于特征融合的UWB AOA估计方法。该方法融合了CIR数据和双天线接收信号特征，并引入Transformer编码器对复杂信号进行深度挖掘，以提升AOA估计的精度。实验结果表明，所提方法在NLOS条件下可以实现高精度的AOA估计。

Abstract

Ultra-wideband (UWB) technology is recognized for its ability to provide high-precision positioning information

offering significant advantages in indoor positioning. Angle of arrival (AOA) estimation

as one of the key technologies in UWB positioning

is considered crucial for improving positioning accuracy. However

in practical applications

UWB AOA estimation is faced with numerous challenges

particularly in complex environments such as non-line-of-sight (NLOS) conditions

antenna hardware impairments and environmental variations. These factors are known to cause signal distortion and measurement deviations

thereby reducing estimation accuracy. Traditional modeling methods are often found inadequate in effectively addressing these nonlinear issues. Therefore

a feature fusion-based UWB AOA estimation method was designed. This approach integrated channel impulse response (CIR) data and dual-antenna received signal features

while a Transformer encoder was introduced to deeply analyze complex signals

thereby enhancing AOA estimation accuracy. Experimental results demonstrated that the proposed method could achieve high-precision AOA estimation under NLOS conditions.

关键词

Keywords

references

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