Analysis of Kalman Filter Approximations for Nonlinear Measurements

Morelande, Mark R and Garcia-Fernandez, Angel F ORCID: 0000-0002-6471-8455 (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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Official URL: https://doi.org/10.1109/tsp.2013.2279367

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:	07 Dec 2024 09:01
DOI:	10.1109/TSP.2013.2279367
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3184157