Analysis of recycling performance in Poisson multi-Bernoulli mixture filters

Abstract

In a multi-target tracking (MTT) scenario, the computational cost of usual Poisson multi-Bernoulli mixture (PMBM) filter will rise rapidly as the increasing number of global hypotheses. In order to lower computational cost, this paper presents to apply recycling algorithm to PMBM filter. The proposed method is done by recycling Bernoulli components which are less than a fixed threshold, approximate them as Poisson point process (PPP), thus add the intensity to the undetected PPP intensity. In the numerical experiment, we apply recycling algorithm to PMBM, Poisson multi-Bernoulli (PMB) and multi-Bernoulli mixture (MBM), respectively. The result shows that the Bernoulli recycling algorithm leads to lower computational cost in a simulated scenario.