计算机科学 ›› 2025, Vol. 52 ›› Issue (11A): 250100083-4.doi: 10.11896/jsjkx.250100083

• 计算机网络 • 上一篇    下一篇

基于UKF的蓝牙-PDR多传感器融合室内定位算法

毛东方1,2, 蒋国平1   

  1. 1 南京邮电大学自动化学院、人工智能学院 南京 210023
    2 无锡真源科技有限公司 江苏 无锡 214135
  • 出版日期:2025-11-15 发布日期:2025-11-10
  • 通讯作者: 毛东方(2022050613@njupt.edu.cn)

Bluetooth-PDR Multi-sensor Fusion Indoor Positioning Method Based on UKF

MAO Dongfang1,2, JIANG Guoping1   

  1. 1 College of Automation & College of Artificial Intelligence,Nanjing University of Posts and Telecommunications,Nanjing 210023,China
    2 Wuxi Realid Technology Co.,Ltd.,Wuxi,Jiangsu 214135,China
  • Online:2025-11-15 Published:2025-11-10

摘要: 为提高室内定位的精度和稳定度,提出了基于无迹卡尔曼滤波(Unscented Kalman Filtering,UKF),并融合蓝牙指纹库和行人航位推算(Pedestrian Dead Reckoning,PDR)的室内定位方法。首先,收集不同位置的信号强度数据,构建蓝牙指纹库。其次,利用手机内置加速度计、陀螺仪等多传感器融合进行行人航位推算。在此基础上使用UKF进行融合,克服行人航位推算易产生累计误差的缺点,从而实现高精度室内定位,具有成本低、灵敏度高、稳定性好、定位方法简便等特点。最后,仿真实验结果表明了该方法的有效性。

关键词: 行人航位推算, 多传感器融合, 无迹卡尔曼滤波, 指纹库, 室内定位

Abstract: To improve the accuracy and stability of indoor positioning,this paper proposes an indoor positioning method based on UKF and by integrating bluetooth fingerprint database and PDR.Firstly,by collecting signal strength data from different locations,a bluetooth fingerprint database is constructed.Secondly,the use of multiple sensors such as built-in accelerometers and gyroscopes in mobile phones for pedestrian dead reckoning is employed.Then,the UKF approach is used for fusion to overcome the disadvantage of cumulative errors in pedestrian dead reckoning,thus achieving high-precision indoor positioning.It has the characteristics of low cost,high sensitivity,good stability,and simple positioning methods.Finally,the experimental simulation results demonstrate the effectiveness of this method.

Key words: PDR, Multi-sensor fusion, Unscented Kalman Filter, Fingerprint Database, Indoor positioning

中图分类号: 

  • TP92
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