Model-based trajectory reconstruction using IMM smoothing and motion pattern identification

This work addresses off-line accurate trajectory reconstruction for air traffic control. We propose the use of specific dynamic models after identification of regular motion patterns. Datasets recorded from opportunity traffic are first segmented in motion segments, based on the mode probabilities of an IMM filter. Then, reconstruction is applied with an optimal smoothing filter operating forward and backward. The parameters describing the specific modes are estimated and then used as external input for smoothing filters. The performance of this approach is compared with a method based on interpolation B-splines. Comparative results on simulated and real data are discussed at the end.