Feasibility analysis of the robust adaptive Kalman filtering model

Abstract

Classic Kalman Filter is a dynamic and efficient data processing method, but there are some limitations. Robust estimation theory will be introduced to the Classical Kalman Filter (CKF) method, that is: Robust Adaptive Kalman Filter (RAKF). There is a clear advantage in reducing the observational errors and the state prediction errors context. In this paper, it uses a dam deformation monitoring example to illustrate that the RAKF is more reliable than the CKF in the deformation monitoring data processing effectively, and it is obviously in inhibiting the aspect of the state prediction errors and the observational errors. It is a viable and effective method of estimation method.