Multidimensional deformation analysis with optimised Kalman filter
Nezhla Aharizad and Halim Setan
The Results of deformation analysis are directly relevant to the safety of human life, hence deformation monitoring and assessing the data of a monitoring network in an optimal way, that is referred to as deformation analysis, help to detect whether deformation exists or not and predict the required maintenance. Filtering means are essential to process the diverse noisy measurements and estimate the parameters of interest. Kalman Filter is one of the means that optimises the state vector minimizing the variance of the estimation error where the measuring process must be able to be described by a linear system. In this study a general description of deformation, the causing factors, requirement of the monitoring, the monitoring and the analyzing techniques are supplied. Afterwards, in order to illustrate 3-D deformation analysis using Kalman Filter (KF), a set of GPS data consists of 3-D coordinates (x, y, z) and time (t) is utilized. A single point test is applied to detect whether a point is stable or not. Later on, the necessity of Extended Kalman Filter (EKF) where the models which relate the parameters to the measurements are non-linear is pointed out.
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