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针对开采沉陷监测中常规RTK测量精度偏低的问题,结合开采沉陷监测的特点,以煤矿开采沉陷自动化监测系统的实时数据采集终端系统2min内各历元采集的坐标及精度为基础,构建卡尔曼滤波模型,以进一步改善移动终端测量精度。利用地表移动观测站的实测数据,通过与常规RTK测量、水准测量结果的比较分析,结果表明滤波后的测量精度得到了较好的改善。从内部符合精度来看,滤波RTK测量的平面位置平均测量精度约为±0.3cm,高程方向平均测量精度约为±0.5cm,完全满足开采沉陷监测的精度要求;与水准测量成果相比,高程方向平均外部测量精度约为±0.8cm,基本满足开采沉陷监测的精度要求。
Aiming at the problem of low precision of conventional RTK measurement in mining subsidence monitoring, combined with the characteristics of mining subsidence monitoring, based on the coordinates and accuracy of each epoch acquired in the real-time data acquisition terminal system of automatic mining subsidence monitoring system, Kalman Filter model to further improve the measurement accuracy of mobile terminals. By using the measured data from observatory of surface movement and comparing with the conventional RTK measurement and level measurement results, the results show that the accuracy of the filtered measurement is better. From the internal compliance accuracy, the average position measurement accuracy of the filter RTK measurement is about ± 0.3cm, and the average accuracy of the elevation direction measurement is about ± 0.5cm, which fully meets the accuracy requirements of mining subsidence monitoring. Compared with the leveling results, The direction of the average external measurement accuracy of about ± 0.8cm, basically meet the mining subsidence monitoring accuracy requirements.