甘肃科学学报

库岸滑坡是滑坡灾害中的重要类型，其滑坡体进入水体后会引发次生涌浪，造成严重的安全威胁。在库岸滑坡监测过程中，全球导航卫星系统(GNSS)面临信号遮挡或测点滑入江中等问题，这可能导致监测数据丢失，进而无法及时响应灾害。为此，提出一种基于惯性测量单元(IMU)与GNSS融合的监测方法，旨在提升监测系统的稳定性与可靠性。首先，通过分析某库区滑坡的监测数据，利用MATLAB对滑入江中的GNSS测点数据进行轨迹拟合，得到了圆弧型滑动轨迹。接着，采用卡尔曼滤波算法实现了IMU与GNSS数据的融合，并进行了基于IMU、GNSS以及IMU融合GNSS 3种监测方式的仿真实验。实验结果表明，IMU与GNSS的融合能够解决GNSS信号更新频率低和信号丢失的问题，抑制IMU误差的累积发散，从而提高滑坡变形监测的精度与稳定性，为库岸滑坡变形监测提供了新的技术手段，以满足灾害预警需求。

Reservoir bank landslides are an important type of landslide disaster.When the landslide mass enters the water, it can trigger secondary waves, posing significant safety threats.During the monitoring of reservoir bank landslides, the Global Navigation Satellite System(GNSS) faces issues such as signal obstruction or monitoring points sliding into the river, which may lead to data loss and inability to response to disaster in a timely manner.To address this, this paper proposes a monitoring method based on the fusion of Inertial Measurement Unit(IMU) and GNSS,aiming to enhance the stability and reliability of the monitoring system.First, by analyzing the monitoring data of a landslide in a reservoir area, the trajectory of the GNSS monitoring points that slid into the river is fitted using MATLAB,resulting in a circular arc sliding trajectory.Then, the Kalman filter algorithm is used to fuse the IMU and GNSS data, and simulations experiments are conducted based on three monitoring methods: IMU,GNSS,and IMU-GNSS fusion.The experimental results indicate that the fusion of IMU and GNSS can solve the issues of low GNSS signal update frequency and signal loss, suppress the cumulative divergence of IMU errors, thus improving the accuracy and stability of landslide deformation monitoring.This provides a new technical approach for reservoir bank landslide deformation monitoring to meet the requirements of disaster early warning.