Kalman最优平滑器在滑坡位移监测数据处理中的应用

针对传统方法中利用Kalman滤波器来处理物体的形变数据存在精度低的缺点,依据Kalman平滑比滤波的精度要高的原理,提出了将滑坡形变的估计问题视为Kalman平滑问题,而不仅仅是Kalman滤波问题;利用Kalman最优平滑器来处理滑坡位移监测数据,可使滑坡预测预报的精度得到较大提高,并在此基础上给出了一种固定区间平滑算法;最后,以龙羊峡龙西滑坡为例进行了实例分析,结果表明本文提出的方法是可行和有效的。此外,结论中针对实际运用中存在的问题提出了相应的建议。

Application of the Best Kalman Smoother in the Monitoring Data Process of the Landslide Displacement

In view of the disadvantage of low precision in the traditional method in which Kalman filter is used to deal with the deformation data of the object and in the light of the theory that Kalman smoothing has a higher precision than its filtering, the problem of the landslide deformation estimation is viewed as not only the Kalman filters problem but also the Kalman smoothers problem in this article. The Kalman smoother is used to deal with the monitoring data of the landslide displacement in order to highly improve the precision of the prediction of landslide, and then a fixed interval smoothing algorithm is given based on the prior study. At last the example of the Longxi landslide in Longyangxia is taken and analyzed, and the analysis of the instance result indicates that the method proposed in the article is feasible and efficient. In the part of the conclusion, the corresponding suggestions are proposed in view of the problem existing in the actual applications.