自适应Kalman滤波在地表沉降观测中的应用

Application of Adaptive Kalman Filtering in the of Surface Subsidence Observations

地下采煤引起的地表沉陷是一个时间和空间的过程,据此提出了观测站动态数据处理模型Kalman滤波和自适应Kalman滤波,通过实例验证了自适应Kalman滤波比普通Kalman滤波在观测站数据滤波和预测中具有优越性。

Surface subsidence caused by underground coal mining is a time and space of the process. This paper put out the proposed observatory dynamic data processing model Kalman filtering and adaptive Kalman filtering at first. And then, the paper verified that adaptive Kalman filtering observatory data than ordinary Kalman filter filtering and forecasting superiority by example.