煤矿井下环境复杂多变，开采过程存在诸多安全隐患。因此，建立一套安全可靠的井下定位系统是完善煤炭安全生产管理的重要手段。针对目前基于测距的煤矿井下定位系统成本高、定位精度低以及环境适应性差等问题，本文对井下定位算法进行了改进并通过仿真和巷道实验，验证了本文改进算法的可行性，具有一定的实际意义和参考价值。本文主要研究工作如下：

（1）针对井下巷道接收信号强度(Received Signal Strength Indicator, RSSI)传输易受多径效应和非视距(Non Line of Sight, NLOS)环境的干扰导致定位精度低的问题，本文围绕RSSI值的预处理、测距模型的建立以及定位算法的改进三个阶段展开研究。首先，在预处理阶段，采用卡尔曼滤波(Kalman Filtering, KF)对RSSI值滤波处理以实现数据的稳定平滑输出。其次，在测距模型建立阶段，采用最小二乘法(Least Square Method, LS)拟合修正信号传播模型参数。最后，在定位算法阶段，优化参考节点选择策略并改进加权质心定位算法。仿真结果表明，本文改进算法平均绝对误差为0.503m，定位误差下降明显。

（2）本文设计了基于ZigBee的井下人员定位系统，使用基于TI公司的ZigBee硬件开发板进行实验验证。利用IAR和Visual Studio开发工具分别对定位系统的下位机和上位机进行程序设计，并将改进的加权质心定位算法引入到上位机进行软件实现。其中上位机能够实现参考节点的预设、盲节点坐标显示等信息。实验结果表明，本文改进算法与仿真结果基本一致，证明了本文改进算法定位的有效性。

本文改进的加权质心定位算法可以有效提高定位精度，对在煤矿井下的实际应用提供了一种有价值的参考。

The underground environment of coal mines is complex and changeable, and there are many safety hazards in the mining process. Therefore, establishing a safe and reliable underground positioning system is an important means to improve coal safety production management. Aiming at the problems of high cost, low positioning accuracy and poor environmental adaptability of the current ranging-based coal mine underground positioning system, this paper improves the underground positioning algorithm and verifies the feasibility of the improved algorithm in this paper through simulation and roadway experiments. Practical significance and reference value. The main research work of this paper is as follows:

(1) Aiming at the problem that the Received Signal Strength Indicator (RSSI) transmission in underground tunnels is susceptible to multipath effects and non-line-of-sight (NLOS) environment interference, which leads to low positioning accuracy, this paper focuses on the RSSI value The preprocessing, the establishment of ranging model and the improvement of localization algorithm are studied in three stages. First, in the preprocessing stage, Kalman Filtering (KF) is used to filter the RSSI value to achieve a stable and smooth output of the data. Secondly, in the stage of establishing the ranging model, the least square method (Least Square Method, LS) is used to fit and correct the parameters of the signal propagation model. Finally, in the positioning algorithm stage, the reference node selection strategy is optimized and the weighted centroid positioning algorithm is improved. The simulation results show that the average absolute error of the improved algorithm in this paper is 0.503m, and the positioning error drops significantly.

(2) This paper designs an underground personnel positioning system based on ZigBee, and uses the ZigBee hardware development board based on TI Company for experimental verification. Using IAR and Visual Studio development tools to program the lower computer and upper computer of the positioning system, and introduce the improved weighted centroid positioning algorithm to the upper computer for software implementation. Among them, the upper computer can realize the preset of reference nodes, coordinate display of blind nodes and other information. The experimental results show that the improved algorithm in this paper is basically consistent with the simulation results, which proves the effectiveness of the improved algorithm in this paper.

The improved weighted centroid positioning algorithm in this paper can effectively improve the positioning accuracy, and provides a valuable reference for the practical application in coal mines.

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