A Numerically Robust Bayesian Filtering Algorithm for Gaussian Mixture Models

Title: A Numerically Robust Bayesian Filtering Algorithm for Gaussian Mixture Models
Creator: Wills, Adrian G.; Hendriks, Johannes; Renton, Christopher; Ninness, Brett
Relation: IFAC-PapersOnLine. Proceedings of the 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS) 2022 [presented in IFAC-PapersOnLine, Vol. 56 No. 1] (Canberra, ACT 04-06 January, 2023) p. 67-72
Publisher Link: http://dx.doi.org/10.1016/j.ifacol.2023.02.012
Publisher: Elsevier
Resource Type: conference paper
Date: 2023
Description: A Bayesian filtering algorithm is developed for a class of state-space systems that can be modelled via Gaussian mixtures. In general, the exact solution to this problem involves an exponential growth in the number of mixture terms and this is handled here by utilising a Gaussian mixture reduction step after both the time and measurement update steps. In addition, a numerically robust square-root implementation of the unified algorithm is presented and this algorithm is profiled on several simulated systems, including the state estimation for a challenging non-linear system.
Subject: Bayesian filtering; gaussian mixture; state-space; linear systems
Identifier: http://hdl.handle.net/1959.13/1494746
Identifier: uon:53878
Language: eng
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