摘要
滑坡是严重的地质灾害,为了降低滑坡灾害,必须对滑坡进行变形监测并给出及时预报。以四川省阿坝州理县通化乡的西山村大型滑坡体GPS监测为例,介绍了GPS滑坡监测数据预处理情况,给出了卡尔曼滤波去噪方法,通过卡尔曼滤波处理前后的坐标分别建立线性预测模型,结果表明,卡尔曼滤波可以很好地去除噪声的影响,使模型的拟合精度较高,模型预测值更接近实际坐标值。
Landslide is a severe geological hazard. In order to ease the landslide disaster, the deformation monitoring of the landslide must be carried out and timely prediction is made. Through Sichuan province ABa County Tonghua town of Xishan village GPS monitoring of large landslide data, this paper introduces the GPS landslide monitoring data preprocessing and denoising method throughthe Kalman Filter.Linear prediction model were established by coordinate before and after filtering the results show that the Kalman Filter can be very useful to ease the influence of noise the fitting precision of the model is high, the model prediction is closer to the actual coordinates.
作者
李海洋
聂桂根
LI Haiyang;NIE Guigen(GNSS Research Center,Wuhan University,Wuhan 430079,China)
出处
《测绘地理信息》
2019年第6期117-119,共3页
Journal of Geomatics
基金
国家重点基础研究发展计划(2013CB733205)
国家自然科学基金(41231174)
武汉市科技局高技术研究计划(2015011701011639)
关键词
GPS监测滑坡
卡尔曼滤波去噪
线性预测模型
精度分析
GPS landslide monitoring
Kalman filter denoising
linearforecasting model
accuracy evaluation