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YOU'RE CROSSING THE LINE: LOCALIZING BORDER CROSSINGS USING WIRELESS RF LINKS

机译:您正在过线:使用无线RF链路本地化边框交叉路口

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Detecting and localizing a person crossing a line segment, i.e., border, is valuable information in security systems and human context awareness. To that end, we propose a border crossing localization system that uses the changes in measured received signal strength (RSS) on links between transceivers deployed linearly along the border. Any single link has a low signal-to-noise ratio because its RSS also varies due to environmental change, (e.g., branches swaying in wind), and sometimes does not change significantly when a person crosses it. The redundant, overlapping nature of the links between many possible pairs of nodes in the network provides an opportunity to mitigate errors. We propose new classifiers to use the redundancy to estimate where a person crosses the border. Specifically, the solution of these classifiers indicates which pair of neighboring nodes the person crosses between. We demonstrate that in many cases, these classifiers provide more robust border crossing localization compared to a classifier that excludes these noisy, redundant measurements.
机译:检测和本地化交叉线段的人,即边框,是安全系统和人类背景知识中的有价值的信息。为此,我们提出了一个边界交叉本地化系统,该系统使用测量的信号强度(RSS)的变化在沿着边界线性部署的收发器之间的链路上。任何单线都具有低信噪比,因为其RS也因环境变化而变化,(例如,风中摇曳的分支),当一个人交叉时,有时不会显着变化。在网络中许多可能对节点的链路之间的冗余,重叠性质提供了减轻错误的机会。我们提出了新的分类器来利用冗余来估计一个人交叉边界的地方。具体地,这些分类器的解决方案表示人在之间的哪个相邻节点。我们展示在许多情况下,与排除这些噪声的分类器相比,这些分类器提供了更强大的边界交叉定位。

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