Estimation of the material budget from tracker data to improve the quality of the track fit

We present two methods to improve the reconstruction of particle tracks by explicit estimates of the amount of material passed by the tracks. The first one is based on a linearized least-squares estimator, the second one on the combination of a forward and a backward Kalman filter. Our simulation studies show that it is possible to obtain a chi-square distribution that is indistinguishable from the one using the true material information. One of the methods has been validated using test beam data. Results of this validation are presented.