Long-Range Trajectory Prediction Errors for Least-Squares Smoothing

This paper presents exact formulas and graphs to determine the root-mean-square error of prediction for position and velocity estimates of an object, based on least-squares smoothing. The prediction interval is taken from an endpoint estimate up to ten times the smoothing interval. The rms values may be used to determine how large a search volume must be to accommodate a substantial data dropout interval.