基于滤波算法的煤矿井下定位技术研究

Study on Positioning Technology in Coal Mines Based on Filtering Algorithms

煤矿井下无线信道容易受到非视距和多径衰落影响,基于RSSI的定位系统误差较大,研究了一种新的井下定位算法。对卡尔曼滤波算法进行研究,抑制测距误差,建立井下信道模型;提出一种协调器节点选取最优参考节点组的方法,利用信道模型和加权最小二乘法确定移动未知节点位置信息;进一步通过扩展卡尔曼滤波算法求精数据,实现煤矿井下矿工及设备的实时定位。井下巷道实验表明,该算法误差控制在3 m以内,提高了定位精度,增强了定位系统的可靠性,可用于煤矿井下定位。

Underground wireless channel in the coal mine is susceptible to non-line-of-sight and multipath fading. Since the error of positioning systems based on RSSI is large, a new underground position algorithm was studied. In the pa- per, ranging error was restrained by Kalman filter algo- rithm, and an underground channel model was established. A method of selecting the best reference node group by coor- dinator nodes was proposed, and location information of mo- bile unknown node was determined by channel model and weighted least square method. Furthermore, extended Kal- man filtering algorithm was adopted to perfect the existing data and to realize the real-time location of coal miners and e- quipments. The underground tunnel experiments showed that the positioning error was restrained in 3 meters, which improved the accuracy and reliability of the system, and the algorithm can be used in the coal mine positioning.