Analysis of Kalman filter approximations for nonlinear measurements

Morelande, MR and García-Fernández, AF (2013) Analysis of Kalman filter approximations for nonlinear measurements IEEE Transactions on Signal Processing, 61 (22). pp. 5477-5484. ISSN 1053-587X, 1941-0476

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Abstract

A theoretical analysis is presented of the correction step of the Kalman filter (KF) and its various approximations for the case of a nonlinear measurement equation with additive Gaussian noise. The KF is based on a Gaussian approximation to the joint density of the state and the measurement. The analysis metric is the Kullback-Leibler divergence of this approximation from the true joint density. The purpose of the analysis is to provide a quantitative tool for understanding and assessing the performance of the KF and its variants in nonlinear scenarios. This is illustrated using a numerical example. © 2013 IEEE.

Item Type:	Article
Uncontrolled Keywords:	Bayesian filtering, Kalman filtering, nonlinear measurement, Kullback-Leibler divergence
Depositing User:	Symplectic Admin
Date Deposited:	02 Sep 2024 08:01
Last Modified:	24 Jan 2026 01:31
DOI:	10.1109/TSP.2013.2279367
Related Websites:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3184157
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