Fast Maneuvering Target Tracking Algorithm with Multiple Passive Sensors
نویسنده
چکیده
For maneuvering target tracking with multiple passive sensors in clutter environment, a novel tracking algorithm based on maximum entropy fuzzy clustering is proposed. Firstly, the interacting multiple models (IMM) approach is used to solve the maneuver problem of the target, and the false alarms generated by clutter are accommodated through maximum entropy fuzzy probabilistic data association filter (MEF-PDAF). Secondly, in order to avoid the unobservability problem of passive target tracking, a nonlinear measurement model of multiple passive sensors is formulated. Moreover, in order to reduce the computational load, the characteristic of the discrimination factor is analyzed, and the influence of the clutter density on it is also considered, which enables the algorithm eliminate those invalidate measurements. Finally, the simulation results show that the proposed algorithm has the advantages over the conventional IMM-PDAF algorithm in terms of simplicity and efficiency.
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