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The main drawback of the cardinalized probability hypothesis density (CPHD) filter is that it can't identify the trajectories of different targets. A data association method, the CPHD filter combined with joint probabilistic data association (JPDA), is presented to track multiple targets in dense clutter. The CPHD filter is used as a pre-filter to remove unlikely measurements before inputting the...
The main drawback of probability hypothesis density (PHD) filter is that it canpsilat identify the trajectories of the different targets. Data association for PHD filter based on multiple hypotheses tracking (MHT) is presented to solve the problem. The track-oriented MHT is used to perform data association on the output of PHD filter. An adaptive Kalman filter based on ldquocurrentrdquo statistic...
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