Improved weighted centroid indoor positioning algorithm for 5G base stations
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摘要: 针对现有基站室内定位算法参与定位基站选择及权重设置不合理导致定位精度低的问题，提出了5G环境下基于接收信号强度指示(RSSI)进行加权质心室内定位算法. 该算法通过RSSI测距得到5个已知基站到待定位点的距离，以已知基站位置为圆心作圆，针对相交所得的五边形区域，取任意3个顶点组成三角形，并根据不同的基站类型以及与待定位点的距离，设定合适权重计算三角形质心坐标，利用所得的10个三角形质心坐标做最大似然估计(MLE)得到最终定位点. 仿真结果表明：在基站稀疏和密集两种环境下，本算法较经典质心算法和加权质心算法，室内定位精度明显提高.
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关键词:
- 基站定位 /
- 5G基站 /
- 接受信号强度指示(RSSI)测距 /
- 加权质心算法 /
- 最大似然估计(MLE)
Abstract: In response to the problem that in existing base station indoor localization algorithm the selection of localization base stations and the unreasonable setting of weights may lead to low localization accuracy, this paper proposes an improved weighted centroid indoor localization algorithm based on received signal strength indicator (RSSI) in the 5G environment. The algorithm obtains the distance from five known base stations to the point to be located by RSSI ranging, and then makes a circle with the known base station location as the centre. For the intersecting pentagonal area, any three vertices are taken to form a triangle. The triangle's centroid coordinates are calculated by setting the appropriate weights according to the type of base station and the distance to the point to be located, and then a maximum likelihood estimation is made based on the ten triangle's centroid coordinates to obtain the final location point. The simulation results show that the indoor localization accuracy of this algorithm is significantly improved when compared with the normal and weighted centroid algorithms in both sparse and dense base station environments. -
表 1 基站密集情况下本文算法与其他算法对比
宏基站是否
参与定位本文算法 经典质心算法 加权质心算法 与标准
位置
距离/m与标准
位置
距离/m本文算法
精度
提高率/%与标准
位置
距离/m本文算法
精度
提高率/%否 2.5271 8.9667 71.8 6.2344 59.4 3.8757 5.4774 29.2 5.0795 23.6 7.3432 11.5553 36.5 8.8115 16.7 3.9596 8.2547 52.1 4.7136 15.9 5.4782 13.9455 60.7 9.0128 39.2 是 10.8367 11.8560 8.6 11.2882 3.9 1.6305 3.8325 57.5 1.6802 3.1 7.2685 12.7018 42.8 7.7365 6.1 10.2600 12.1816 15.8 10.7177 4.3 7.7502 8.4058 7.8 8.0708 4.0 
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表 2 基站稀疏情况下本文算法与其他算法对比
宏基站是否
参与定位本文算法 经典质心算法 加权质心算法 与标准
位置
距离/m与标准
位置
距离/m本文算法
精度
提高率/%与标准
位置
距离/m本文算法
精度
提高率/%否 4.1076 5.2460 21.7 4.8111 14.6 4.3919 5.0141 14.2 4.9463 12.6 4.4210 7.1497 38.1 5.0052 13.2 7.1131 11.5950 38.7 8.7905 19.1 3.0576 5.1545 40.7 3.7536 18.5 是 7.2685 13.8017 47.3 7.7000 5.2 13.6932 18.1158 24.2 14.7015 7.3 5.4758 11.6225 52.9 5.8112 5.7 6.1806 18.4341 66.5 7.0576 12.4 1.9305 3.7345 48.3 2.1802 11.5
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