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CSI-Based Indoor Localization

机译：基于CSI的室内本地化

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摘要

Indoor positioning systems have received increasing attention for supporting location-based services in indoor environments. WiFi-based indoor localization has been attractive due to its open access and low cost properties. However, the distance estimation based on received signal strength indicator (RSSI) is easily affected by the temporal and spatial variance due to the multipath effect, which contributes to most of the estimation errors in current systems. In this work, we analyze this effect across the physical layer and account for the undesirable RSSI readings being reported. We explore the frequency diversity of the subcarriers in orthogonal frequency division multiplexing systems and propose a novel approach called FILA, which leverages the channel state information (CSI) to build a propagation model and a fingerprinting system at the receiver. We implement the FILA system on commercial 802.11 NICs, and then evaluate its performance in different typical indoor scenarios. The experimental results show that the accuracy and latency of distance calculation can be significantly enhanced by using CSI. Moreover, FILA can significantly improve the localization accuracy compared with the corresponding RSSI approach.
机译：室内定位系统在室内环境中支持基于位置的服务已受到越来越多的关注。基于WiFi的室内本地化由于其开放式访问和低成本特性而吸引人。但是，由于多径效应，基于接收信号强度指示符（RSSI）的距离估计很容易受到时间和空间变化的影响，这会导致当前系统中的大多数估计误差。在这项工作中，我们分析了整个物理层的这种影响，并说明了报告的不良RSSI读数。我们探索正交频分复用系统中子载波的频率分集，并提出一种称为FILA的新方法，该方法利用信道状态信息（CSI）在接收器处建立传播模型和指纹识别系统。我们在商业802.11 NIC上实施FILA系统，然后评估其在不同典型室内场景中的性能。实验结果表明，使用CSI可以显着提高距离计算的准确性和时延。此外，与相应的RSSI方法相比，FILA可以显着提高定位精度。

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