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Rollout Algorithms for the Measurement-to-Track Association Problem

Ozgen, Selim
Demirekler, Mübeccel
The quality and precision of tracking manuevering targets under large clutter is highly dependent on both the data association and state estimation algorithms. In this study, measurement-to track association problem was discussed and the optimal association problem was shown to be a Markov Decision Process. The problem model considers the batch measurements in a time interval. The optimization problem has an heavy computational load, therefore the rollout algorithm is used to solve this problem. The approximate solution to the association problem is a new approach and it does not exist in the literature. The algorithm was applied to a tracking scenario and its efficiency is demonstrated in the simulations part.