基于变维滤波算法的Kalman最佳平滑器在滑坡监测数据处理中的应用

Application of the Optimal Kalman Smoother Based on Variable Dimension Filter Algorithm in Landslide Monitor Data Process

本文研究如何对滑坡监测数据进行去噪。利用变维滤波算法能够很好描述滑坡变形的特性,建立了滑坡运动的数学模型,并引入变维滤波对滑坡监测数据进行降噪。为了提高滑坡预报精度,提出了一种基于变维滤波的Kalman最佳平滑算法。实例仿真结果表明利用该方法不仅预报精度高,而且也为寻找滑坡监测数据中的变点提供了新的思路。

The paper studies methods about reducing the noise of landslide monitor data. It is indicated that the variable dimension filter algorithm can exactly simulate the landslide locomotion, and a mathematical model of landslide locomotion is built. A VD algorithm is introduced to filter the landslide monitor data. In order to improve the prediction precision, an optimal smooth algorithm of Kalman filter is given. The results show that the method improves the landslide prediction precision and offers a new way to find the inflexion in the landslide monitor data.