摘要
为合理利用边坡的几何信息和物理信息,控制几何观测异常对形变参数估计的影响,建立了一种带有未知系统误差的滤波模型,并给出了一种基于移动窗口的系统误差自适应拟合法,同时给出了相应的状态预测向量的协方差矩阵估计方法。GPS监测网的计算结果表明,该算法可以通过拟合地球物理信息来减弱观测异常所带来的影响,提高形变参数解算精度。
To take advantage of geometric and physical information of slopes and restrain the influence of the observation outliers on the estimates of deformation parameters,a filtering model handling unknown systematic errors is developed.An adaptive fitting algorithm for the systematic errors based on moving windows is presented and the estimation method for covariance matrices of the predicted states is given.The presented algorithm utilizes the statistical information of observations as well as landslide related information such as mechanics status and geological conditions.The results of the GPS monitoring network show that the algorithm may reduce the effect of abnormal observation by fitting the geophysical information,and therefore improve the precision of deformation parameter estimates.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2012年第1期86-90,共5页
Geomatics and Information Science of Wuhan University
基金
国家自然科学基金资助项目(40874005)
国家教育部博士点专项基金资助项目(200805331086)
关键词
系统误差
边坡
变形监测
卡尔曼滤波
systematic errors
slope
deformation monitoring
Kalman filter
