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基于模糊逻辑和 WLAN 基础设施的室内定位系统。

Indoor Positioning System Based on Fuzzy Logic and WLAN Infrastructure.

机构信息

Department of Telecommunications Engineering, Czech Technical University in Prague, Technická 2, 166 27 Praha 6, Czech Republic.

Department of Economics and Control Systems, VSB-Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava-Poruba, Czech Republic.

出版信息

Sensors (Basel). 2020 Aug 11;20(16):4490. doi: 10.3390/s20164490.

Abstract

This paper deals with the issue of mobile device localization in the environment of buildings, which is suitable for use in healthcare or crisis management. The developed localization system is based on wireless Local Area Network (LAN) infrastructure (commonly referred to as Wi-Fi), evaluating signal strength from different access points, using the fingerprinting method for localization. The most serious problems consist in multipath signal propagation and the different sensitivities (calibration) of Wi-Fi adapters installed in different mobile devices. To solve these issues, an algorithm based on fuzzy logic is proposed to optimize the localization performance. The localization system consists of five elements, which are mobile applications for Android OS, a fuzzy derivation model, and a web surveillance environment for displaying the localization results. All of these elements use a database and shared storage on a virtualized server running Ubuntu. The developed system is implemented in Java for Android-based mobile devices and successfully tested. The average accuracy is satisfactory for determining the position of a client device on the level of rooms.

摘要

本文讨论了建筑物环境中移动设备定位的问题,该定位适用于医疗保健或危机管理。所开发的定位系统基于无线局域网 (LAN) 基础设施(通常称为 Wi-Fi),通过使用指纹定位方法评估来自不同接入点的信号强度。最严重的问题在于多径信号传播和安装在不同移动设备中的 Wi-Fi 适配器的不同灵敏度(校准)。为了解决这些问题,提出了一种基于模糊逻辑的算法来优化定位性能。定位系统由五个元素组成,它们是适用于 Android OS 的移动应用程序、模糊推导模型以及用于显示定位结果的网络监控环境。所有这些元素都使用数据库和共享存储在运行 Ubuntu 的虚拟化服务器上。所开发的系统是在 Java 中实现的,用于基于 Android 的移动设备,并已成功测试。对于确定客户端设备在房间级别上的位置,平均精度令人满意。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9986/7472030/22f98dd0ef54/sensors-20-04490-g001.jpg

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