This paper demonstrates the feasibility of received power strength indicator (RSSI)-based single-antenna localization (R-SAL) with decimeter-level localization accuracy. To achieve decimeter-level accuracy, either fine-grained radio frequency (RF) information (e.g., channel state information) or coarse-grained RF information (e.g., RSSI) from more than multiple antennas is required. Meanwhile, owing to deficiency of single-antenna RSSI which only indicates a distance between a receiver and a transmitter, realizing fine-grained localization accuracy with single coarse-grained RF information is challenging. Our key idea to address this challenge is to leverage computer vision (CV) and to estimate the most likely Fresnel zone between the receiver and transmitter, where the role of RSSI is to detect blockage timings. Specifically, historical positions of an obstacle that dynamically blocks the Fresnel zone are detected by the CV technique, and we estimate positions at which a blockage starts and ends via a time series of RSSI. These estimated obstacle positions, in principle, coincide with points on the Fresnel zone boundaries, enabling the estimation of the Fresnel zone and localization of the transmitter. The experimental evaluation revealed that the proposed R-SAL achieved decimeter-level localization in an indoor environment, which is comparable to that of a simple previous RSSI-based localization with three receivers.

中文翻译：

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利用动态阻塞事件的计算机视觉辅助分米级单天线 RSSI 定位

本文论证了基于接收功率强度指标 (RSSI) 的单天线定位 (R-SAL) 具有分米级定位精度的可行性。为了实现分米级精度，需要来自多个天线的细粒度射频 (RF) 信息（例如，信道状态信息）或粗粒度 RF 信息（例如，RSSI）。同时，由于单天线RSSI仅指示接收器和发射器之间的距离的不足，用单个粗粒度RF信息实现细粒度定位精度具有挑战性。我们应对这一挑战的关键想法是利用计算机视觉 (CV) 并估计接收器和发射器之间最可能的菲涅耳区域，其中 RSSI 的作用是检测阻塞时间。具体来说，通过 CV 技术检测动态阻塞菲涅耳区域的障碍物的历史位置，我们通过 RSSI 时间序列估计阻塞开始和结束的位置。这些估计的障碍物位置原则上与菲涅耳区域边界上的点重合，从而能够估计菲涅耳区域和定位发射机。实验评估表明，所提出的 R-SAL 在室内环境中实现了分米级定位，这与之前使用三个接收器的简单的基于 RSSI 的定位相当。与菲涅耳区域边界上的点重合，从而能够估计菲涅耳区域和定位发射机。实验评估表明，所提出的 R-SAL 在室内环境中实现了分米级定位，这与之前使用三个接收器的简单的基于 RSSI 的定位相当。与菲涅耳区域边界上的点重合，从而能够估计菲涅耳区域和定位发射机。实验评估表明，所提出的 R-SAL 在室内环境中实现了分米级定位，这与之前使用三个接收器的简单的基于 RSSI 的定位相当。