改进卡尔曼滤波的井下组合导航定位算法

为解决井下人员定位算法定位精度不高的问题,提出基于微惯性导航系统和无线传感器网络的井下组合导航定位算法.通过井下无线网络、惯性定位终端采集相关信息数据,利用行人航迹推算算法和改进加权质心定位算法分别估算出目标点的坐标和速度.将这两种算法通过正弦余弦蝙蝠融合算法优化后的卡尔曼滤波组合导航定位,估算出目标点最终的位置坐标....

UNDERGROUND INTERGRATED NAVIGATION POSITIONING ALGORITHM BASED ON IMPROVED KALMAN FILER

In order to solve the problem of low positioning accuracy of underground personnel positioning algorithm,an underground integrated navigation positioning algorithm based on micro-inertial-navigation system and wireless sensor networks is proposed.We collected relevant information data through underground wireless network and inertial positioning terminal,and estimated the coordinates and speed of target points respectively by using pedestrian track estimation algorithm and improved weighted centroid positioning algorithm.The two algorithms were located by Kalman filter integrated navigation optimized by Sine cosine bat fusion algorithm,and the final position coordinates of the target point were estimated.The experimental results show that the average positioning error of the integrated navigation positioning algorithm is 1.71 m,and its positioning accuracy is higher than that of the traditional centroid positioning algorithm and pedestrian trajectory estimation algorithm.