A PMBM Forward-Backward Smoother for Multiple Extended Targets

This paper presents a Poisson multi-Bernoulli mixture (PMBM) forward-backward smoother for multiple extended target detection and tracking in the random finite sets (RFS) framework. The proposed method consists of forward filtering, achieved by the PMBM filter recursion, followed by backward smoothing, achieved by a parametric updated posterior PMBM density. The performance of the proposed method is evaluated in a simulation study.