A Gaussian Sum Filter-based indoor localization algorithm using bluetooth beacons
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摘要: 高精度的室内定位是物联网中基于位置服务应用的基础. 低功耗蓝牙信标的接收信号强度指标(RSSI)可用于室内定位. 为此，提出基于高斯和滤波的蓝牙信标室内定位(GSF-IL)算法. GSF-IL算法考虑到室内环境信号的多径衰落以及波动，利用高斯和滤波(GSF)算法处理RSSI测量值，使RSSI值具有非高斯特性，并利用瓦瑟斯坦距离(WD)将GSF模型的分量数降至单高斯分量. 仿真结果表明：提出的GSF-IL算法实现对原始RSSI值的修正作用，并利用了定位精度.
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关键词:
- 室内定位 /
- 瓦瑟斯坦距离(WD) /
- 接收信号强度指标(RSSI) /
- 高斯和滤波(GSF) /
- 巴氏距离
Abstract: High precision indoor localization is the basis of location based service in Internet of Thing. The received signal strength indicator (RSSI) values of bluetooth low energy (BLE) can be used to do analysis and computation in location system. Therefore, Gaussian sum filter-based indoor localization used bluetooth beacons (GSF-IL) is proposed in this paper. Considering the multipath fading and fluctuation of indoor environmental signals, the Gaussian sum filter (GSF) is used to process the RSSI measurement value, so that the RSSI value has non-Gaussian characteristics, and the Wasserstein distance (WD) is used to reduce the component number of the GSF model to a single Gaussian component. Simulation results show that the proposed GSF-IL algorithm can modify the original RSSI value and make use of the positioning accuracy. -
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