通信学报 ›› 2018, Vol. 39 ›› Issue (12): 47-59.doi: 10.11959/j.issn.1000-436x.2018280

• 学术论文 • 上一篇    下一篇

VehLoc:基于低功耗蓝牙多信道RSSI值的车内高精度定位方法

赵泽1,高源1,2,崔莉1()   

  1. 1 中国科学院计算技术研究所,北京 100190
    2 中国科学院大学计算与控制学院,北京 100049
  • 修回日期:2018-07-26 出版日期:2018-12-01 发布日期:2019-01-21
  • 作者简介:赵泽(1978–),男,锡伯族,辽宁大连人,博士,中国科学院计算技术研究所高级工程师,主要研究方向为嵌入式系统、无线传感器网络、物联网。|高源(1993–),女,黑龙江鸡西人,中国科学院大学硕士生,主要研究方向为传感器技术。|崔莉(1962–),女,北京人,博士,中国科学院研究员、博士生导师,主要研究方向为传感器技术、无线传感器网络。
  • 基金资助:
    国家自然科学基金资助项目(No.61672498);国家自然科学基金资助项目(No.61502461)

VehLoc: an in-vehicle high-precision location method based on BLE multi-channel RSSI values

Ze ZHAO1,Yuan GAO1,2,Li CUI1()   

  1. 1 Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
    2 School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • Revised:2018-07-26 Online:2018-12-01 Published:2019-01-21
  • Supported by:
    The National Natural Science Foundation of China(No.61672498);The National Natural Science Foundation of China(No.61502461)

摘要:

高精度车内定位技术是提供车内智能服务、进行车内用户行为习惯分析等应用的基础,有重要实用价值。低功耗蓝牙(BLE, bluetooth low energy)的RSSI(received signal strength indicator)值可用于定位系统的分析计算。针对无线信号传输易受环境影响的问题,对车内定位提出了一种基于蓝牙多信道多RSSI值(multi-channel multi-RSSI values)的车内定位方法 VehLoc。接收端在传统的采集蓝牙 RSSI 信号的基础上,同时记录信号的信道来源,通过使用3个蓝牙信标在其不同信道的RSSI值对使用者终端在车内的位置进行粗细粒度与分布相结合的区域分析和位置判断。实验结果表明,VehLoc定位方法对车内5个主要位置的分类正确率均可达90%。

关键词: 低功耗蓝牙, 多信道, 接收信号强度指示, 分类, 拟合

Abstract:

High precision in-vehicle positioning is the basis of providing smart in-vehicle service, passengers' behavior analysis and other issues, and has important practical value. The RSSI (received signal strength indicator) values of BLE (bluetooth low energy) can be used to do analysis and computation in location system. To deal with the problem that RSSI is vulnerable to environmental issues, an in-vehicle location method called VehLoc based on BLE multi-channel multi-RSSI values was proposed. By using a plurality of Bluetooth transmitters, the location of the receiving terminals in the vehicle was analyzed by combining the coarse, fine classifier and distribution fitting of the user's RSSI values in different channels. The experimental results show that the average accuracy of VehLoc in the five main positions in-vehicle classification can reach 90%.

Key words: BLE, multi-channel, RSSI, classification, fitting

中图分类号: 

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