摘要
激光雷达(LiDAR)和超宽带(UWB)是目前常用的井下定位技术。针对在矿井巷道等结构特征稀疏且连续重复的场景下,单一LiDAR定位因几何约束信息不足而导致定位偏差、UWB定位易受非视距(NLOS)误差影响导致定位精度下降的问题,提出一种基于DS证据理论的井下UWB/LiDAR组合定位方法。以信道统计参数中的信号能量作为特征参数,采用核密度估计法进行特征提取;依据提取的能量特征,采用模拟退火−支持向量机(SA−SVM)对NLOS环境进行识别,实现对UWB定位中NLOS误差的有效处理;采用DS证据理论对UWB和LiDAR定位数据进行融合,以提高定位精度。在某煤矿井下巷道进行实验,结果表明:SA−SVM对NLOS环境的识别准确率达94%;基于DS证据理论的UWB/LiDAR组合定位方法的最大误差为1.07350 m,最小误差为0.00205 m,平均误差为0.25934 m,标准差为0.11005 m,均方根误差为0.33108 m,优于UWB定位、LiDAR定位和基于扩展卡尔曼滤波的组合定位方法。
LightLaser Detection and Ranging(LiDAR)and Ultra Wide Band(UWB)are currently widely used underground positioning technologies.To address the problem that single LiDAR positioning in mine roadways with sparse and repetitive structural features produces deviations due to insufficient geometric constraints,and UWB positioning is prone to accuracy degradation caused by Non-Line-of-Sight(NLOS)errors,this paper proposed an underground UWB/LiDAR integrated positioning method based on DS evidence theory.Signal energy in channel statistical parameters was used as the feature parameter,and kernel density estimation was employed for feature extraction.Based on the extracted energy features,Simulated Annealing-Support Vector Machine(SA-SVM)was applied to identify NLOS environments,achieving effective handling of NLOS errors in UWB positioning.DS evidence theory was then adopted to fuse UWB and LiDAR positioning data to improve positioning accuracy.Experiments were carried out in an underground roadway of a coal mine.The results showed that SA-SVM achieved 94%accuracy in NLOS environment identification.The maximum error of the UWB/LiDAR integrated positioning method based on DS evidence theory was 1.07350 m,the minimum error was 0.00205 m,the mean error was 0.25934 m,the standard deviation was 0.11005 m,and the root mean square error was 0.33108 m.This method outperforms UWB positioning,LiDAR positioning,and the integrated positioning method based on Extended Kalman Filter.
作者
姚肃良
孟玮
YAO Suliang;MENG Wei(Yaojie Coal&Electricity Group Tianzhu Coal Industry Co.,Ltd.,Wuwei 733200,China;CCTEG Changzhou Research Institute,Changzhou 213015,China;Tiandi(Changzhou)Automation Co.,Ltd.,Changzhou 213015,China)
出处
《工矿自动化》
北大核心
2025年第8期74-79,122,共7页
Journal of Mine Automation
基金
江苏省科技成果转化项目(BA2022040)。
关键词
井下定位
UWB定位
LiDAR定位
DS证据理论
组合定位
underground positioning
UWB positioning
LiDAR positioning
DS evidence theory
integrated positioning
