Gaussian implementation of the multi-Bernoulli mixture filter

Garcaa-Fernandez, AF, Xia, Y, Granstrom, K, Svensson, L and Williams, JL (2019) Gaussian implementation of the multi-Bernoulli mixture filter In: 22nd International Conference on Information Fusion, 2019-7-2 - 2019-7-5, Ottawa.

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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.

Item Type:	Conference Item (Unspecified)
Additional Information:	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
Uncontrolled Keywords:	eess.SP, eess.SP, cs.CV, stat.AP
Depositing User:	Symplectic Admin
Date Deposited:	12 Jun 2019 08:59
Last Modified:	25 Jul 2026 08:40
DOI:	10.23919/FUSION43075.2019.9011346
Related Websites:	Author
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3045515
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