可扩展的基于Wi-Fi的本地化方法

T. Le, N. Nguyen
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引用次数: 6

摘要

本文提出了一种可扩展的方法,允许在不同的设备上部署指纹Wi-Fi定位算法。原始的指纹定位算法只有在测试阶段使用的设备与训练阶段使用的设备相同的情况下才能准确执行。当在测试阶段使用不同的设备时,需要一个耗时的重新训练步骤(按小时或天的顺序)才能达到同等程度的准确性。我们提出的方法用短时间的校准(大约几分钟)取代了重新训练步骤,这对用户来说是透明的。为了验证我们的方法,我们从一个大规模的实验中收集数据(14台笔记本电脑和2台智能手机,收集了224小时的数据)来评估性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A scalable Wi-Fi based localization approach
This paper proposes a scalable method which allows deploying the fingerprint Wi-Fi localization algorithm for different devices. The original fingerprint localization algorithm performs accurately only if the device used in the testing phase is the same as the device used in the training phase. When a different device is used in the testing phase, a time-consuming re-training step (in the order of hours or days) is required to achieve the equivalent degree of accuracy. Our proposed approach replaces the re-training step with a short period of calibration (in the order of a few minutes), which can be done transparently to the user. To validate our approach, we collected data from a large scale experiment (14 laptops and 2 smartphones with 224-hour of collected data) to evaluate the performance.
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