On the relation between Gaussian process quadratures and sigma-point methods
Artikel i vetenskaplig tidskrift, 2016

This article is concerned with Gaussian process quadratures, which are numerical integration methods based on Gaussian process regression methods, and sigma-point methods, which are used in advanced non-linear Kalman filtering and smoothing algorithms. We show that many sigma-point methods can be interpreted as Gaussian process quadrature based methods with suitably selected covariance functions. We show that this interpretation also extends to more general multivariate Gauss-Hermite integration methods and related spherical cubature rules. Additionally, we discuss different criteria for selecting the sigma-point locations: exactness of the integrals of multivariate polynomials up to a given order, minimum average error, and quasi-random point sets. The performance of the different methods is tested in numerical experiments.

Författare

A. S. Arkkä

Aalto-Yliopisto

J. Hartikainen

Rocsole Ltd

Lennart Svensson

Chalmers, Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Fredrik Sandblom

Volvo Group

Journal of Advances in Information Fusion

1557-6418 (ISSN)

Vol. 11 31-46

Ämneskategorier

Elektroteknik och elektronik