A Hybrid Method to Improve the BLE-Based Indoor Positioning in a Dense Bluetooth Environment
A Hybrid Method to Improve the BLE-Based Indoor Positioning in a Dense Bluetooth Environment
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DOI：
10.3390/s19020424
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发表时间：
2019-01-02
期刊：
影响因子：
3.9
通讯作者：
Du, Xuecheng
中科院分区：
文献类型：
--
作者：
Huang, Ke;He, Ke;Du, Xuecheng
使用蓝牙低功耗（BLE）信标的室内定位在BLE协议发布后引起了相当大的关注。已经做出了许多努力来改善基于BLE的室内定位的性能。然而，很少有研究关注基于BLE的室内定位在密集的蓝牙环境中，其中BLE信号的传播变得更加复杂和更加波动。在本文中，我们提请注意的问题，从密集的蓝牙环境，它原来是密集的蓝牙环境会导致高的接收信号强度指示（RSSI）的变化和长时间间隔收集的BLE。因此，为了减轻密集蓝牙环境的影响，我们提出了一种混合方法融合滑动窗口滤波，三边测量，航位推算和卡尔曼滤波方法，以提高BLE室内定位的性能。利用卡尔曼滤波融合三边测量和航位推算。在一个真实的实施进行了广泛的实验，以检查三种方法的性能：三边测量，航位推算和融合方法。实验结果表明，在密集蓝牙环境下，融合方法是提高定位精度和实时性的最有效方法。定位均方根误差（RMSE）计算结果表明，该混合方法可以实现实时定位，降低室内定位误差。
Indoor positioning using Bluetooth Low Energy (BLE) beacons has attracted considerable attention after the release of the BLE protocol. A number of efforts have been exerted to improve the performance of BLE-based indoor positioning. However, few studies pay attention to the BLE-based indoor positioning in a dense Bluetooth environment, where the propagation of BLE signals become more complex and more fluctuant. In this paper, we draw attention to the problems resulting from the dense Bluetooth environment, and it turns out that the dense Bluetooth environment would result in a high received signal strength indication (RSSI) variation and a longtime interval collection of BLE. Hence, to mitigate the effects of the dense Bluetooth environment, we propose a hybrid method fusing sliding-window filtering, trilateration, dead reckoning and the Kalman filtering method to improve the performance of the BLE indoor positioning. The Kalman filter is exploited to merge the trilateration and dead reckoning. Extensive experiments in a real implementation are conducted to examine the performance of three approaches: trilateration, dead reckoning and the fusion method. The implementation results proved that the fusion method was the most effective method to improve the positioning accuracy and timeliness in a dense Bluetooth environment. The positioning root-mean-square error (RMSE) calculation results have showed that the hybrid method can achieve a real-time positioning and reduce error of indoor positioning.