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On the Crucial Impact of Antennas and Diversity on BLE RSSI-Based Indoor Localization

机译:天线和分集对基于BLE RSSI的室内定位的关键影响

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Due to their low complexity, RSSI-based solutions for indoor localization have become increasingly popular in recent years despite lacking the accuracy of more sophisticated localization solutions. One of the main reasons for this lack of accuracy is the highly fluctuating nature of RSSI values as a result of indoor channel characteristics, hardware imperfections and varying antenna radiation patterns. In this paper, we thus critically analyze the log- normal path loss model and its validity with the focus on indoor localization. We show how chip antennas of typical consumer devices affect the RSSI measurements and clarify in what manner this effect can be incorporated into the log-normal model. In this process, we are also able to quantify the impact of small-scale fading and diversity on RSSI-based distance estimation. We furthermore propose a novel calibration scheme that estimates path loss exponents based on a simple training walk and outperforms linear regression in all our use cases. At last, we combine our findings in an implementation of an indoor localization system for a 14×3 m office corridor. On average, our measurements yield a significantly decreased position RMSE of 1.36 m, which compares to the Cramer- Rao lower bound on the position RMSE of 0.71 m in this environment.
机译:由于其复杂性低,尽管缺乏更复杂的本地化解决方案的准确性,但基于RSSI的室内本地化解决方案近年来变得越来越流行。缺乏准确性的主要原因之一是由于室内信道特性,硬件缺陷和不断变化的天线辐射方向图,导致RSSI值高度波动。因此,在本文中,我们着重分析了对数正态路径损耗模型及其有效性,重点是室内定位。我们展示了典型消费类设备的芯片天线如何影响RSSI测量,并阐明了以何种方式可以将这种影响纳入对数正态模型。在此过程中,我们还能够量化小规模衰落和分集对基于RSSI的距离估计的影响。我们还提出了一种新颖的校准方案,该方案可基于简单的训练步伐估算路径损耗指数,并且在所有用例中均优于线性回归。最后,我们结合我们的发现,为14×3 m的办公室走廊实施室内定位系统。平均而言,在这种环境下,我们的测量结果得出,RMSE的位置显着降低了1.36 m,而Cramer-Rao位置RMSE的下限为0.71 m。

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