Chan-Kalman算法在井下定位中的应用研究  

Research on the Application of the Chan Kalman Algorithm in Underground Positioning

作　　者：王开松[1,2] 张亮[1,2] 徐记顺[1,2] 许欢 WANG Kaisong;ZHANG Liang;XU Jishun;XU Huan(State Key Laboratory of Mining Response and Disaster Prevention and Control in Deep Coal Mines,Anhui University of Science and Technology,Huainan 232001,China;School of Mechanical Engineering,Anhui University of Science and Technology,Huainan 232001,China)

机构地区：[1]安徽理工大学深部煤矿采动响应与灾害防控国家重点实验室,安徽淮南232001 [2]安徽理工大学机械工程学院,安徽淮南232001

出　　处：《景德镇学院学报》2023年第6期1-5,共5页Journal of JingDeZhen University

基　　金：国家重点研发计划(2020YFB1314103)。

摘　　要：针对井下环境存在的非视距误差而导致超宽带定位技术精度降低的问题,对可抑制定位误差的Chan-Kalman算法进行了研究。该算法基于TOA定位模型,通过Chan算法对标签位置坐标进行初步解算,再采用卡尔曼滤波算法对初步解算结果进行优化,最终得出较为精确的标签位置坐标。实验结果表明,该算法明显提高了超宽带定位系统的定位精度。To address the issue of reduced accuracy in Ultra wideband positioning technology due to non line of sight errors in underground environments,research has been conducted on the Chan Kalman algorithm,designed to mitigate positioning inaccuracies.This algorithm is grounded in the Time of Arrival positioning model.It utilizes the Chan algorithm to initially estimate the coordinates of tag locations and subsequently refines these estimates through the Kalman filtering algorithm,and finally a notably more precise set of tag location coordinates are obtained.Experimental findings confirm that this algorithm significantly enhances the accuracy of UWB positioning systems.

关 键 词：井下定位 超宽带 CHAN算法 卡尔曼滤波 

分 类 号：TD655[矿业工程—矿山机电]