Multitarget tracking using probability hypothesis density smoothing
In general, for multitarget problems where the number of targets and their states are time varying, the optimal Bayesian multitarget tracking is computationally demanding. The Probability Hypothesis Density (PHD) filter, which is the first-order moment approximation of the optimal one, is a computat...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/17753 |