利用新息构造AKF估计和预报大坝变形

Construct AKF to Improve Precision of Estimating and Predicting Dam Deformation Using Innovation

利用线形流形的射影方法推导出新息序列统计特性,构造新息AKF,基于新息序列不断地修正状态噪声和量测噪声,实时地反映模型当前真实的统计特性。通过隔河岩大坝实测数据处理,表明该方法能很好地提高随机模型不准确和变形突变影响下的变形估计与预报精度。

The Kalman filter（KF） method is propitious to process the dynamic dam deforma- tion monitoring data. However, the state noise （R） and survey noise （Q） in the deformation monitoring is difficult to be provided precisely, the standard Kalman Filter method is con- fined. This article presents AKF based on innovation statistic properties to modify the R and Q, and to reflect correct statistic properties of current model by real time. With a dam survey data, this method succeed to overcome imprecision of stochastic model and deformation salta- tion to improve the precision of estimation and prediction in dam deformation.