带定位盲区的矿井人员全局无线定位算法

Personnel Global Wireless Positioning Algorithm in Mine with Positioning Blind

针对目前现有的矿井人员定位系统只能局部定位,定位精度不高,存在定位盲区等问题,提出了一种改进的井下人员全局无线定位算法。首先阐述了一种矿井人员局部无线定位算法,为减小多径效应、环境干扰等环境因素影响,对其进行了最大似然估计滤波优化,在此基础上,通过坐标变换提出了一种新型的井下人员全局无线定位算法。在矿井定位盲区,应用卡尔曼滤波器对井下人员的惯性定位和无线定位信息进行融合,实现井下人员定位在定位盲区和非定位盲区的平滑过渡。仿真结果表明该算法能对井下人员进行全局定位,在定位盲区能对人员位置进行预测,具有较好的定位精度。

An improved global wireless underground personnel positioning algorithm is proposea against some existing problems such as local positioning, poor positioning accuracy and positioning blind in the current mine personnel positioning system. Firstly, a local wireless location algorithm is described, and a maximum likelihood estimation optimization filter is used to reduce the impact of multipath effects, environmental interference etc., based on this, a new global wireless underground personnel positioning algorithm is then proposed through the coordinate transformation. A Kalman filter is applied to the positioning blind in the mine to fuse the underground personnel positioning information for inertial positioning and wireless location to achieve the smooth transition between positioning blind and non-blind. The simulation results show that the algorithm not only works well to the global underground personnel positioning, but also predicts the personnel positions in positioning blind with good accuracy.