A Kalman Filter for Track-based Alignment
Veröffentlicht am 31.01.2006 in CMS Note
An iterative method for track-based global alignment is proposed. It is derived from the Kalman filter and is designed to avoid the inversion of large matrices. The update formulas for the alignment parameters and for the associated covariance matrix are described. The implementation and the computational complexity is discussed, and it is shown how to limit the latter to an acceptable level by restricting the update to detectors that are close in the sense of a certain metrics. The performance of the Kalman filter with respect to precision and speed of convergence is studied in a simplified setup. First results from an implementation in the CMS reconstruction program ORCA are presented, using two sections of the barrel part of the CMS Tracker.
Autoren: Edmund Widl
Kategorie: Reviewed Paper