A Tractable Forward- Backward CPHD Smoother

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

Abstract: 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.