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A statistical study on the impact of wireless signals' behavior on location estimation accuracy in 802.11 fingerprinting systems

机译:802.11指纹系统中无线信号行为对位置估计准确性的影响的统计研究

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Much of the recent interest in location estimation systems has focused on 802.11 fingerprinting. Unlike GPS systems, 802.11 based systems can accurately estimate a user's location inside buildings. Moreover, users don't need any special equipment to carry around, as their WiFi enabled cell phone can already act as the receiver in WiFi fingerprinting systems. However, wireless access points in buildings are placed mostly according to another criteria, namely to increase the network coverage inside the building. But optimal coverage may not necessarily result in optimal location discovery. In this paper, we provide analyses on data gathered for a real WiFi location estimation system, and show what makes it perform inaccurately in some parts of a building while it is more accurate in other parts. We have defined two new metrics for quantifying the wireless signal behavior of multiple access points in small neighborhoods in a building. Finally, we identify the properties that differentiate well behaving and poorly behaving neighborhoods.
机译:最近对位置估计系统的兴趣集中在802.11指纹识别上。与GPS系统不同,基于802.11的系统可以准确估算用户在建筑物内的位置。此外,用户不需要携带任何特殊设备,因为具有WiFi功能的手机已经可以充当WiFi指纹系统中的接收器。但是,建筑物中的无线接入点大多是根据另一个标准放置的,即增加建筑物内部的网络覆盖范围。但是最佳覆盖范围不一定会导致最佳位置发现。在本文中,我们将对为一个真实的WiFi位置估计系统收集的数据进行分析,并说明是什么导致它在建筑物的某些部分运行不准确,而在其他部分运行更准确。我们已经定义了两个新指标,用于量化建筑物中较小社区中多个接入点的无线信号行为。最后,我们确定区分良好行为和不良行为邻域的属性。

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