中文摘要：

无线传感网（WSN）在矿井人员定位应用中受到多径干扰与机电噪声的影响,其定位精度不高.针对常规定位跟踪算法的抗干扰技术进行优化处理,提出了一种用于矿井中对工作人员定位跟踪的滤波优化算法（LO-EKF）.结合惯性测量系统（IMU）和加权质心定位算法（WCL）来估计目标人员的状态参量,再通过经统计协方差矩阵配置过的扩展卡尔曼滤波器（EKF）对状态参量进行优化处理,得出最终的目标位置.仿真表明,对比定位误差累积分布函数图,LO-EKF算法相对于传统EKF算法在矿井定位中不仅能保障短期精度,而且能有效提高长期精度.

英文摘要：

When Wireless Sensor Network（ WSN） is applied to personnel positioning in mine,because of the influence of multipath interference and mechanical electrical noise,its location accuracy is usually not high.To optimize the anti-interference technology used in conventional positioning and tracking algorithms,this paper proposes an optimized Extended Kalman Filtering algorithm（ LO-EKF） for positioning workers in the mine.This algorithm combines the inertial measurement unit（ IMU） with the weighted centroid localization algorithm（ WCL） to estimate the parameters of the states of target workers,and then processes and optimizes these parameters through an extended Kalman filter（ EKF） configured by statistical covariance matrix,in order to get final target position. Simulation results show that,compared to location errors of the cumulative distribution function（ CDF）,LO-EKF algorithm with respect to the traditional EKF algorithm not only protect the short-term high accuracy,but also improve the long-term accuracy.