ComputingComputer ScienceComputer VisionFeature EngineeringMachine LearningData AssociationKalman FilteringSignal Detection TheoryVisual TrackingClutter Map EstimationClutter Statistics ModelingData Association In Radar TrackingProbabilistic Data AssociationRadar Data AssociationTarget Tracking
An intelligent probabilistic data association filter (IPDAF) is presented as a refinement of the original IPDAF developed by D. Musicki et al. (1994). The refinement includes the incorporation of measurement feature information, a better estimator of clutter density, and an important correction of a mistake in the original PDAF and IPDAF. Simulation results demonstrate the substantial superiority of the proposed IPDAF to the original one.
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