中国安全科学学报 ›› 2026, Vol. 36 ›› Issue (4): 204-210.doi: 10.16265/j.cnki.issn1003-3033.2026.04.0177

• 公共安全与应急管理 • 上一篇    下一篇

面向应急救援的BP神经网络人员定位-追踪-静止报警系统

王丽1(), 王喆1, 关文玲1, 张嘉琪1, 刘超林2, 孟玉莹1,3   

  1. 1 天津理工大学 环境科学与安全工程学院, 天津 300384
    2 应急管理部信息研究院, 北京, 100029
    3 山东锦维安恒教育科技有限公司, 山东 济南 250003
  • 收稿日期:2025-12-14 修回日期:2026-02-26 出版日期:2026-05-12
  • 作者简介:

    王 丽 (1982—),女,山东泰安人,博士,讲师,硕士生导师,主要从事人群疏散、公共安全、应急管理等方面的研究。E-mail:

    关文玲, 副教授

    张嘉琪, 教授

    刘超林, 高级工程师

  • 基金资助:
    国家自然科学基金面上项目资助(52074192); 天津市科技计划项目(24YDTPJC00110)

BP neural network-based personnel positioning-tracking-stationary alarm system for emergency rescue

Wang Li1(), Wang Zhe1, Guan Wenling1, Zhang Jiaqi1, Liu Chaolin2, Meng Yuying1,3   

  1. 1 School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300384, China
    2 Information Research Institute of Ministry of Emergency Management (MEM), Beijing 100029, China
    3 Shandong Jinweianheng Education Technology Co., Ltd., Ji'nan Shandong 250003, China
  • Received:2025-12-14 Revised:2026-02-26 Published:2026-05-12

摘要:

为及时救治火场中被困人员,提出一种耦合反向传播(BP)神经网络和双侧双向测距(DS-TWR)技术的室内人员定位-追踪-及静止报警系统。该系统利用实验室虚拟仪器工程工作台(LabVIEW)整合超宽带(UWB)的DS-TWR技术和BP神经网络,通过BP神经网络学习多径效应与非视距传播的误差特征,修正DS-TWR误差,精确定位人员位置,同步记录行动轨迹;通过计算人员在指定时间范围内的移动距离来评估运动状态,设定位移与时间阈值构建报警机制,当检测到人员静止超过安全阈值时系统自动触发报警。结果表明:该系统在正常及金属障碍电磁干扰环境下,静态及动态定位误差可达厘米级,具有定位精度高、稳定性好的优势,且轨迹绘制精准,人员静止报警信息准确,响应延迟控制在较低水平。

关键词: 应急救援, 反向传播(BP)神经网络, 人员定位-追踪-静止报警, 双侧双向测距(DS-TWR), 实验室虚拟仪器工程工作台(LabVIEW)

Abstract:

To ensure timely rescue of trapped personnel in fire scenarios, a personnel positioning-tracking-stationary alarm system was proposed by combining BP neural networks and DS-TWR technology. The system was developed based on the LabVIEW platform, where the BP neural network learned the error patterns of multipath effects and non-line-of-sight propagation, corrected DS-TWR ranging errors, and achieved precise personnel positioning and trajectory tracking. By calculating the movement distance within a defined time, the system evaluated personnel motion status and established thresholds of displacement and time to trigger alarms, which automatically activated alerts when a person remained stationary beyond the safety threshold. Test results show that the system achieves centimeter-level static and dynamic positioning accuracy under both normal and metal/electromagnetic interference environments. It features high positioning precision and favorable stability, enables accurate trajectory generation, delivers reliable static personnel alarms, and maintains a low response latency.

Key words: emergency rescue, back propagation (BP) neural network, personnel positioning-tracking-stationary alarm, double-sided two-way ranging (DS-TWR), laboratory virtual instrument engineering workbench (LabVIEW)

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