Railway track geometry determination using adaptive Kalman filtering model

The Kalman filter has been widely used to solve different filtering problems especially in tracking and estimation applications. Besides its simplicity, robustness and optimality, the application of Kalman filter to nonlinear systems can be complicated. The most common method is to use extended Kalman filter which linearizes the nonlinear model so that the standard Kalman filter can be applied. In this paper, a new adaptive Kalman filtering algorithm is designed and applied to a railway track geometry surveying system which has been designed in the scope of a research project at Yildiz Technical University/Turkey. Track gauge, super-elevation, gradient and track axis coordinates which are the railway geometrical parameters can be instantly determined while making measurements by using adaptive Kalman filtering algorithm integrated surveying system.

► A new multi-sensor railway track geometry surveying system has been designed.
► We also designed new software which operates with the surveying system in real time.
► An adaptive Kalman filtering model was designed.
► Railway track geometry was determined by using this adaptive Kalman filtering model.
► The standards of International Union of Railways have been achieved with this system.