Gaussian implementation of the multi-Bernoulli mixture filter
Abstract
This paper presents the Gaussian implementation of the multi-Bernoulli mixture (MBM) filter. The MBM filter provides the filtering (multi-target) density for the standard dynamic and radar measurement models when the birth model is multi-Bernoulli or multi-Bernoulli mixture. Under linear/Gaussian models, the single target densities of the MBM mixture admit Gaussian closed-form expressions. Murty's algorithm is used to select the global hypotheses with highest weights. The MBM filter is compared with other algorithms in the literature via numerical simulations.
Keywords
Cite
@article{arxiv.1908.08819,
title = {Gaussian implementation of the multi-Bernoulli mixture filter},
author = {Ángel F. García-Fernández and Yuxuan Xia and Karl Granström and Lennart Svensson and Jason L. Williams},
journal= {arXiv preprint arXiv:1908.08819},
year = {2019}
}
Comments
Matlab code of the MBM and PMBM filters is provided in https://github.com/Agarciafernandez/MTT . Additional information on MTT including PMBM and MBM filters can be found in the online course https://www.youtube.com/channel/UCa2-fpj6AV8T6JK1uTRuFpw