Filtered Gate Structure Applied to Joint Probabilistic Data Association Algorithm for Multi-Target Tracking in Dense Clutter Environment
In multi-target tracking system (MTT) Improving data association process in the presence of severe clutter are discussed in this paper. New technique in dense clutter environment based on filtering gate method applied to conventional approaches as joint probabilistic data association filter (JPDAF) is introduced to overcome the issue that the data association algorithm begins to fail due to the increase in background clutter and false signals. An adaptive search based on the distance threshold measure is then used to detect valid filtered data point for multi-target tracking. Simulation results demonstrate the effectiveness and better performance when compared to conventional algorithm.
Keywords: Data Association, Multi-Target Tracking, Joint Probabilistic Data Association Algorithm, Filtering
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