基于北斗的相对位移测量方法在滑坡监测中的设计与实现

Design and Implementation of Beidou-based Relative Displacement Measurement Method in Landslide Monitoring

摘要:

滑坡的相对位移测量是滑坡监测预警的重中之重，针对测量中实时连续监测难、测量精度不稳定等问题，采用了一种基于北斗导航定位数据的相对位移测量方法，应用卡尔曼滤波平滑测量过程中的噪声保证数据稳定连续，使用导航数据处理软件RTKLIB中的RTKNAVI工具对定位数据进行RTK处理提高定位精度，解算出滑坡相对位移量；并在所介绍测量方法的依据下设计了测量设备硬件平台，对设备进行了模拟滑坡测量试验，结果表明：依据此方法优化设计的测量设备定位精度在水平方向精度为5mm，垂直方向精度为1.5cm，相对位移测量精度在4mm内，滑坡倾角测量精度达到0.01°，数据平均有效率为96.97%，测量过程稳定连续，能够满足滑坡监测中的相对位移测量需要，且该方法可以用来监测滑坡的单次和累积位移量，将位移量与角度变化量相结合可以很好反映滑坡前兆与趋势，为滑坡监测预警提供可靠判据。

Abstract:

Relative seismic measurement of landslides is the top priority in landslide monitoring and early warning. In order to solve the problems of difficulty in real-time continuous monitoring and unstable measurement accuracy, a relative seismic measurement method based on Beidou navigation and positioning data is adopted, and Kalman-assisted smoothing is applied. The noise during the measurement process ensures that the data is stable and continuous. The RTKNAVI tool in the navigation data processing software RTKLIB is used to perform RTK processing on the positioning data to improve the positioning accuracy and calculate the relative displacement of the landslide. The measurement method is designed based on the introduction of the measurement method. Equipment hardware platform, a simulated landslide measurement test was conducted on the equipment. The results show that the positioning accuracy of the measurement equipment optimized using this method is 5mm in the horizontal direction, 1.5cm in the vertical direction, the relative bearing measurement accuracy is within 4mm, and the landslide inclination angle measurement The accuracy reaches 0.01°, the average effective data meets 96.97%, and the measurement process is stable and continuous, which can meet the needs of relative seismic measurement in landslide monitoring. This method can be used to monitor the single and cumulative earthquake volume of landslides, and combine the seismic volume with the angle change. The combination can well reflect the precursors and trends of landslides and provide reliable judgment basis for landslide monitoring and early warning.