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- W2142575747 abstract "The probability hypothesis density (PHD) filter is a practical alternative to the theoretically optimal multi-target Bayesian filter based on random finite sets (RFS) for multi-target tracking. In this paper, we propose Track PHD (TPHD) filter based on a track state space consisted of target position history and it propagates the multi-target intensity function of track RFS. The new filter provides the estimates of target track states and makes it easy to confirm identities. Simulation results demonstrate TPHD filter is effective in estimating multi-target states and providing target identities even when targets are in close proximity." @default.
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- W2142575747 date "2011-05-01" @default.
- W2142575747 modified "2023-10-17" @default.
- W2142575747 title "Track probability hypothesis density filter for multi-target tracking" @default.
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- W2142575747 doi "https://doi.org/10.1109/radar.2011.5960610" @default.
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