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基于AKF-AM-Bi-GRU优化的UWB室内定位方法

王鹏华 苏治文 史航 陈绍益 金枫翔

云南民族大学学报(自然科学版)2026,Vol.35Issue(1):98-106,9.
云南民族大学学报(自然科学版)2026,Vol.35Issue(1):98-106,9.DOI:10.3969/j.issn.1672-8513.2026.01.012

基于AKF-AM-Bi-GRU优化的UWB室内定位方法

UWB indoor positioning method based on AKF-AM-Bi-GRU optimization

王鹏华 1苏治文 2史航 1陈绍益 1金枫翔1

作者信息

  • 1. 云南省烟草公司曲靖市公司,云南曲靖 655000
  • 2. 昆明理工大学交通工程学院,云南 昆明 650504
  • 折叠

摘要

Abstract

Aiming at the problem of low accuracy of UWB positioning technology in indoor complex environment,a UWB indoor positioning method based on AKF-AM-Bi-GRU optimization is proposed.Firstly,adaptive Kalman filter based on residual adjustment is used to reduce the influence of signal noise and outliers on UWB plositioning accuracy.Secondly,AM Bi GRU is used to deeply mine the time series characteristics in the historical distance value data to optimize the distance value from the tag point to each base station.Then,the weight of the least squares method is adjusted in combination with the standard deviation of the historical distance value,and the coordinates of the label points are calculated using the weighted least squares method.Finally,it is verified by setting up several groups of real indoor scene experiments,and summarizes the positioning error.The experimental results show that the positioning accuracy of UWB is improved by 44.45%on average after optimized UWB positioning by adaptive Kalman filter based on residual adjustment;Compared with AKF and AKF-AM-Bi-LSTM,the positioning accuracy of AKF-AM-Bi-GRU has increased by 59.08%and 16.35%on average,and the positioning error has reached 5.051 6 cm and 10.034 6 cm in sight distance and non sight distance environments.The proposed method effectively improves the accuracy and robustness of UWB positioning in indoor complex environment,and achieves better positioning results.

关键词

室内定位/超宽带/自适应卡尔曼滤波/Bi-GRU/注意力机制/非视距误差

Key words

indoor positioning/ultra wide band/adaptive kalman filter/Bi-GRU/attention mechanism/NLOS error

分类

信息技术与安全科学

引用本文复制引用

王鹏华,苏治文,史航,陈绍益,金枫翔..基于AKF-AM-Bi-GRU优化的UWB室内定位方法[J].云南民族大学学报(自然科学版),2026,35(1):98-106,9.

基金项目

云南省烟草公司曲靖市公司科技计划项目(2023YNQJKJ01). (2023YNQJKJ01)

云南民族大学学报(自然科学版)

1672-8513

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