Information Exchange track-before-detect Multi-Bernoulli filter for superpositional sensors

Davies, Elinor S and Garcia-Fernandez, Angel ORCID: 0000-0002-6471-8455 (2024) Information Exchange track-before-detect Multi-Bernoulli filter for superpositional sensors. IEEE Transactions on Signal Processing, 72. pp. 1-15.

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Official URL: http://dx.doi.org/10.1109/tsp.2024.3349769

Abstract

In this paper we derive the Information Exchange track-before-detect Multi-Bernoulli (IEMB) filter for multi-target filtering with superpositional sensors. The IEMB filter propagates a multi-Bernoulli density through the filtering recursion and each Bernoulli is propagated with its own prediction and update step. At each update step, each Bernoulli filter exchanges the predicted mean and covariance matrix of its measurement contribution with the other Bernoulli filters. The exchanged information is then used by the filters to perform the update step. Additionally, we propose the Iterated Posterior Linearisation Filter (IPLF) implementation of the IEMB filter (IEMB-IPLF). We compare the IEMB-IPLF filter to a number of other non-linear filtering methods showing the benefits of the proposed filter.

Item Type:	Article
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	15 Jan 2024 08:36
Last Modified:	15 Mar 2024 13:54
DOI:	10.1109/tsp.2024.3349769
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3177830