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User Tracking for Access Control with Bluetooth Low Energy

机译:用户跟踪低功耗蓝牙访问控制

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The Received Signal Strength Indicator (RSSI) of Bluetooth Low Energy (BLE) is a popular means for indoor user localization and tracking as it reflects the transmitter-receiver distance and is readily available in all current smartphones. Since fading, shadowing and antenna patterns cause severe RSSI fluctuations, many RSSI-based localization systems use fingerprinting instead of parameter estimation based on a channel model (e.g. trilateration from distance estimates). Fingerprinting however requires a large effort for training data acquisition and frequent updates in dynamic environments. In this paper we focus on wireless access control with BLE. We demonstrate that a practical implementation of such a tracking system can meet the typical demands of generic access control problems with low- complexity parameter estimation techniques, namely trilateration and optional Kalman filtering. Thereby, satisfactory accuracy is enabled by diversity (averaging in space, time and frequency), calibration and appropriate observation space modeling. We find that including the RSSI directly in the observation space renders trilateration obsolete, which reduces complexity even further.
机译:蓝牙低功耗(BLE)的接收信号强度指示器(RSSI)是室内用户定位和跟踪的一种流行手段,因为它反映了收发器之间的距离,并且在所有当前的智能手机中都可以轻松获得。由于衰落,阴影和天线方向图会导致严重的RSSI波动,因此许多基于RSSI的定位系统都使用指纹识别来代替基于信道模型的参数估计(例如,距离估计的三边测量)。但是,在动态环境中,指纹识别需要花费大量精力来训练数据获取和频繁更新。在本文中,我们重点介绍BLE的无线访问控制。我们证明,这种跟踪系统的实际实现可以使用低复杂度参数估计技术(即三边测量和可选的Kalman滤波)来满足一般访问控制问题的典型需求。因此,通过多样性(空间,时间和频率的平均值),校准和适当的观察空间建模,可以获得令人满意的精度。我们发现直接在观测空间中包含RSSI会使三边测量过时,从而进一步降低了复杂度。

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