Approximate multisensor CPHD and PHD filters

@article{Mahler2010ApproximateMC,
  title={Approximate multisensor CPHD and PHD filters},
  author={Ronald P. S. Mahler},
  journal={2010 13th International Conference on Information Fusion},
  year={2010},
  pages={1-8}
}
The probability hypothesis density (PHD) filter and cardinalized probability hypothesis density (CPHD) filter are principled approximations of the general multitarget Bayes recursive filter. Both filters are single-sensor filters. Since their multisensor generalizations are computationally intractable, a further approximation - iterating their corrector equations, once for each sensor - has been used instead. This approach is theoretically unpleasing because it is not invariant under reordering… CONTINUE READING
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Statistical Multisource-Multitarget Information Fusion

  • R. Mahler
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1 Excerpt

Multitarget filtering via first-order multitarget moments

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