基于统计接收信号强度(RSS)模型的指纹定位方法在WLAN室内定位中的应用

2019 21st International Conference on Advanced Communication Technology (ICACT) Pub Date : 2019-02-01 DOI:10.23919/ICACT.2019.8701972

Mai A. Abd El-Halim, A. M. Said, Hadia M. El-Hennawy

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引用次数: 2

摘要

本文建立了一种新的统计接收信号强度(RSS)模型，用于指纹离线模式和在线模式下的准确定位。该模型采用极差法和中差法，给出了新的均值和标准差。同时，计算了RSS信号的频率分布模式，并将其用于RSS模型中。在Android智能手机上开发了WLAN室内定位应用程序，用于检测准确的位置。该应用程序在埃及开罗纳斯尔城的City Center Mall进行测试，并使用该Mall的未知位置接入点(ap)。本文提出的RSS模型被应用于指纹离线模式下测试区域无线地图的构建。在指纹在线模式下，采用一种新的搜索方法，将无线地图的预定义位置与在线位置进行匹配。结果表明，除部分位置定位不准确外，其他位置定位准确。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A New Statistical Received Signal Strength (RSS) Model Based Fingerprint Approach for WLAN Indoor Localization Application

In this paper, a new statistical received signal strength (RSS) model is formulated to be used in fingerprint offline mode and online mode for detecting the location accurately. The range and the midrange methods are used in this model that gives a new mean and standard deviation as called in this paper. Also, the frequency distribution patterns are calculated for RSS signals and used in RSS model. WLAN Indoor localization application is developed on Android Smartphone to be used in detecting the accurate location. The application is tested in City Center Mall in Nasr City, Cairo, Egypt and used the unknowing location access points (APs) of this MALL. The RSS model of this paper is used by the application for constructing the radio map of testing area in fingerprint offline mode. In fingerprint online mode, a new searching method is used for matching between the predefined locations of radio map and the online locations. The results give the accurate location correctly except some locations are not determined well.

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来源期刊

2019 21st International Conference on Advanced Communication Technology (ICACT)

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