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Multiple-target tracking in a cluttered environment and intelligent track record

The foremost difficulty in the Multiple Target Tracking (MTT) field involves the problem of associating the measurements with the tracks when there are missing reports and the proliferation of false reports generated by clutter. In this paper, in order to solve this return-to- track association as-well-as the estimation problem, we are proposing to associate Artificial Intelligence techniques and Signal Processing method. The Signal Processing method is the Multiple Hypothesis Filter (M.H.F.).