高效WiFi指纹训练使用半监督学习

Ye Yuan, L. Pei, Changqing Xu, Qianchen Liu, Tingyu Gu
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引用次数: 13

摘要

基于指纹识别的WiFi定位方法需要一个离线训练阶段,利用每个参考点接收到的信号强度指示向量构建无线电波图。在现有的系统中,为了获得满意的定位结果,这一训练阶段可能会花费大量的工作量。为了显著减少工作量,同时保证定位结果,我们将引入一种高效的WiFi指纹训练方法:Fa-Fi,即快速指纹生成,本文采用半监督学习。该方法在保证定位精度的前提下,将训练阶段时间成本降低到1/5左右。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient WiFi fingerprint training using semi-supervised learning
Fingerfrinting based WiFi positioning approach needs an off-line training phase to build a radio map with received signal strength indication vector of each reference point. In existing systems, this training phase may cost a tremendous amount of workload to achieve satisfying location result. To cut down on the workload notably and guarantee the location result in the meantime, we will introduce an efficient WiFi fingerprint training method: Fa-Fi namely fast fingerprint generation, which uses semi-supervised learning in this article. This proposed method can reduce the training phase time cost to about 1/5, and guarantee the localization accuracy at the same time.
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