Study on Improved Algorithm of RSSI Correction and Location in Mine-well Based on Bluetooth Positioning Information

Yadi Wu, Senlin Cheng, Xiaohao Yan
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引用次数: 2

Abstract

In order to overcome positioning accuracy being lower of Bluetooth caused by the uncertainty and other interference factors under the mine well environment, the paper proposed an improved RSSI correction location algorithm based on Bluetooth positioning information. The algorithm firstly carried on the data pre-filtering based on secondary filter to reduce the gross error and interference of RSSI sampled data, secondly built a piecewise path loss model based on sliding window by means of logarithmic path loss model to fit the relationship between distance and RSSI better, and finally integrated Bluetooth positioning information into the improved fine weight three-circle positioning to estimate the unknown node location accurately. Taking the corridor-type mine well environment as an example, the experimental data verified that the method could effectively reduce the ranging error, and the highest positioning accuracy could reach to 0.11 meter, and compared with the general weighted triangular centroid positioning method, its average error could reduce about 27%. The study results show that the proposed improvement method in this paper is reasonable and feasible.
基于蓝牙定位信息的井下RSSI校正与定位改进算法研究
针对矿井环境下蓝牙定位精度不确定等干扰因素导致定位精度较低的问题,本文提出了一种基于蓝牙定位信息的改进RSSI校正定位算法。该算法首先进行基于二次滤波的数据预滤波,降低RSSI采样数据的粗误差和干扰,其次利用对数路径损失模型构建基于滑动窗口的分段路径损失模型,更好地拟合距离与RSSI之间的关系,最后将蓝牙定位信息集成到改进的细权三圆定位中,准确估计未知节点位置。以巷道式矿井环境为例,实验数据验证了该方法能有效减小测距误差,最高定位精度可达0.11 m,与一般加权三角质心定位方法相比,其平均误差可减小27%左右。研究结果表明,本文提出的改进方法是合理可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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