基于多特征融合的RFID标签实时准确定位

Shupo Fu, Shigeng Zhang, Danming Jiang, Xuan Liu
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引用次数: 0

摘要

我们提出一种新的射频识别(RFID)定位方法,通过融合多种类型的信号特征来实现低延迟和高精度。现有的RFID标签定位方法要么存在较大的定位延迟(例如,基于相位测量的方法),要么无法提供高定位精度(例如,基于接收信号强度(RSS)的方法)。我们提出了一种融合相位测量和RSS测量的两步方法来解决这一难题。首先,使用粗粒度的RSS测量来找出包含目标标记位置的小边界框。其次,使用细粒度相位测量来改进目标标签在边界框中的位置估计。实验结果表明,所提出的融合方法在不到10个特征测量值的情况下实现了厘米级的定位精度,与目前的解决方案相比,将定位延迟降低了一个数量级以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time and Accurate RFID Tag Localization based on Multiple Feature Fusion
We propose a new radio frequency identification (RFID) localization approach that achieves both low latency and high accuracy by fusing multiple type of signal features. Existing RFID tag localization approaches either suffer from large localization latency (e.g., approaches based on phase measurements), or cannot provide high localization accuracy (e.g., approaches based on received signal strength (RSS)). We propose a two-step approach that fuses phase measurements and RSS measurements to resolve this dilemma. First, coarse-grained RSS measurements are utilized to Figure out a small bounding box that encloses the position of the target tag. Second, fine-grained phase measurements are used to refine the position estimation of the target tag in the bounding box. Experimental results show that the proposed fusion approach achieves centimeter-level localization accuracy with less than 10 feature measurements, reducing localization latency by more than one order of magnitude when compared to state-of-the-art solutions.
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