Gating Techniques for Rao-Blackwellized Monte Carlo Data Association Filter

Abstract

This paper studies the Rao-Blackwellized Monte Carlo data association (RBMCDA) filter for multiple target tracking. The elliptical gating strategies are redesigned and incorporated into the framework of the RBMCDA filter. The obvious benefit is the reduction of the time cost because the data association procedure can be carried out with less validated measurements. In addition, the overlapped parts of the neighboring validation regions are divided into several separated subregions according to the possible origins of the validated measurements. In these subregions, the measurement uncertainties can be taken into account more reasonably than those of the simple elliptical gate. This would help to achieve higher tracking ability of the RBMCDA algorithm by a better association prior approximation. Simulation results are provided to show the effectiveness of the proposed gating techniques.

Combining particle MCMC with Rao-Blackwellized Monte Carlo data association for parameter estimation in multiple target tracking

“…This research could be continued in several directions. To speed up computations, one could combine gating techniques with RBMCDA (Wang and Zhang, 2014). It may be possible to derive an upper bound for the measurement likelihoods such that early rejection (Solonen et al, 2012) could be applied in RBMCDA-PMMH.…”