A data decorrelation method for 3D position measurements from a line sensors based photogrammetric measuring system

In this study, a data decorrelation method is developed for processing 3D position measurements obtained by a line sensors based photogrammetric measuring system. The measured 3D data suffer from correlations due to the principle of the triangulation. This nature causes complexity when a calibration procedure is carried out. Additionally, the correlated data may affect its further exploration and applications, such as robot visual servoing. For this reason, a data decorrelation method based on multivariate statistical analysis is proposed to preprocess the 3D coordinate measurements, in such a way that each component of the coordinate can be treated individually. Consequently, the calibration procedure can be significantly simplified in a less time and memory consuming manner. The proposed method includes the local and global data decorrelation. Evaluation and comparisons of these two approaches have been analyzed with a conclusion on the better performance of the global data decorrelation. The optimal decorrelated configuration based on the results has been identified for the measuring system.