基于运动学约束模型辅助的井下人员定位系统研究  

Research on Positioning System for Underground Mine Personnel Based on Kinematics Constraint Model

作　　者：高春雷[1] 赵宾[1,2] 吴崇 GAO Chun-lei;ZHAO Bin;WU Chong(Jincheng College, Nanjing University of Aeronautics and Astronautics, Nanjing 211156, China;College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China;Wuhan Design and Research Institute Co., Ltd., China Coal Technology and Engineering Group, Wuhan 430064, China)

机构地区：[1]南京航空航天大学金城学院,南京211156 [2]南京航空航天大学自动化学院,南京211106 [3]中国煤炭科工集团武汉设计研究院有限公司,武汉430064

出　　处：《煤炭技术》2019年第6期170-172,共3页Coal Technology

摘　　要：针对井下人员定位中MEMS微惯性导航系统定位误差较大,而卫星信号无法使用的问题,研究了一种基于运动学约束模型辅助的井下人员定位系统。构建了井下人员运动学约束模型,根据人体步行的特点,采用载体系下的速度输出作为量测信息,通过卡尔曼滤波融合方法估计出导航以及传感器误差,并进行反馈校正,提高井下人员定位系统的精度。实验结果表明:定位误差约为总行进距离的3%,证明了所提出的方法可有效提高井下人员定位精度,在无外界辅助信息可用的井下环境中,实现较长时间的自主实时定位。The positioning error of the MEMS inertial navigation system is large and the satellite signal is not available in positioning of underground mine personnel. To solve this problem, a positioning system for underground mine personnel based on kinematic constraint model is proposed. The kinematic constraint model of underground mine personnel is constructed, and according to the characteristics of walking process, the velocity of the carrier coordinate system is used as measurement information directly. The Kalman filter fusion method is used to estimate the navigation and sensor errors, and the accuracy of positioning system of underground mine personnel is improved by feedback tunning. The experiment results show that, the positioning error take up 3% of the whole distances of walking respectively. The experiment conclusion proves that the proposed method can effectively improve the positioning precision of underground mine personnel, and can achieve autonomous and real-time positioning for longer time under the mine environment that external auxiliary information is not available.

关 键 词：MEMS微惯性导航系统 井下人员定位 运动学约束 滤波融合 

分 类 号：TD67[矿业工程—矿山机电] TD76