A Tractable Forward-Backward CPHD Smoother

Sharad Nagappa, Emmanuel D. Delande, Daniel E. Clark, Jeremie Houssineau

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)
25 Downloads (Pure)


To circumvent the intractability of the usual Cardinalized Probability Hypothesis Density (CPHD) smoother, we present an approximate scheme where the population of targets born until and after the starting time of the smoothing are estimated separately and where smoothing is only applied to the estimate of the former population. The approach is illustrated through the implementation of a tractable approximation of the usual CPHD smoother.

Original languageEnglish
Pages (from-to)201-217
Number of pages17
JournalIEEE Transactions on Aerospace and Electronic Systems
Issue number1
Publication statusPublished - 9 Jan 2017


  • Finite set statistics (FISST)
  • forward-backward smoothing
  • multi-object filtering
  • probability hypothesis density (PHD)/cardinalized probability hypothesis density (CPHD) filters

ASJC Scopus subject areas

  • Aerospace Engineering
  • Electrical and Electronic Engineering


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