无线局域网中与设备无关的基于指纹定位的3D光线追踪

M. Raspopoulos, C. Laoudias, L. Kanaris, Akis Kokkinis, C. Panayiotou, S. Stavrou
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引用次数: 44

摘要

我们研究了使用3D射线追踪(RT)来构建无线局域网接收信号强度(RSS)指纹定位的放射图,并结合校准技术使整个过程与设备无关。RSS数据收集可能是一个繁琐而耗时的过程,而且测量的无线电地图的准确性和适用性也受到无线环境中潜在变化的影响。因此,RT成为一种更有吸引力和更有效的生成放射性地图的方法。此外,传统的基于指纹的方法导致无线电地图被限制在用于生成无线电地图的设备上,并且在考虑不同的设备时无法提供可接受的性能。我们通过利用3D rt生成的无线电地图和使用线性数据转换来匹配各种设备的特征来解决这两个挑战。我们根据创建无线电地图所花费的时间、为不同设备校准无线电地图所需的数据量以及与使用每个设备收集的专用无线电地图的情况相比的定位误差来评估这种方法的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Ray Tracing for device-independent fingerprint-based positioning in WLANs
We study the use of 3D Ray Tracing (RT) to construct radiomaps for WLAN Received Signal Strength (RSS) fingerprint-based positioning, in conjunction with calibration techniques to make the overall process device-independent. RSS data collection might be a tedious and time-consuming process and also the measured radiomap accuracy and applicability is subject to potential changes in the wireless environment. Therefore, RT becomes a more attractive and efficient way to generate radiomaps. Moreover, traditional fingerprint-based methods lead to radiomaps which are restricted to the device used to generate the radiomap and fail to provide acceptable performance when different devices are considered. We address both challenges by exploiting 3D RT-generated radiomaps and using linear data transformation to match the characteristics of various devices. We evaluate the efficiency of this approach in terms of the time spent to create the radiomap, the amount of data required to calibrate the radiomap for different devices and the positioning error which is compared against the case of using dedicated radiomaps collected with each device.
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