Prediction of surface movement deformation based on Kalman filtering
XU Zhe-ming
Abstract：Aiming at the operation divergence problem caused by the fact that the traditional Kalman filtering model in the prediction of surface deformation depends on the noise and mathematical models, a prediction analysis method of building surface movement deformation based on adaptive Kalman filtering with variance compensation was proposed. The proposed adaptive Kalman filtering could compensate the deficiency of noise variance in the filtering process mainly through appropriately estimating and correcting the uncertain parameters of the system model and the statistical properties of the noise. The mathematical model for adaptive Kalman filtering was established, and the simulation analysis for the prediction of surface movement deformation was performed with Matlab software. The results verify the feasibility of the proposed Kalman filtering method in the prediction of surface movement deformation. The proposed method effectively improves the reliability and forecasting precision of real-time prediction.
Keywords：surface deformationKalman filteringvariance compensationadaptionpredictionmathematical modelMatlab simulationreliability
Publication Date：2017-09-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 557-561 )