The scaled unscented transformation

This paper describes a generalisation of the unscented transformation (UT) which allows sigma points to be scaled to an arbitrary dimension. The UT is a method for predicting means and covariances in nonlinear systems. A set of samples are deterministically chosen which match the mean and covariance...

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Bibliographic Details
Main Author: Julier, S.J.
Format: Conference Proceeding
Language:English
Subjects:
Applied sciences
Cities and towns
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
Filtering
Filters
Gaussian distribution
Jacobian matrices
Nonlinear systems
Random variables
Sampling methods
Statistics
Uncertainty
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Description
Summary:This paper describes a generalisation of the unscented transformation (UT) which allows sigma points to be scaled to an arbitrary dimension. The UT is a method for predicting means and covariances in nonlinear systems. A set of samples are deterministically chosen which match the mean and covariance of a (not necessarily Gaussian-distributed) probability distribution. These samples can be scaled by an arbitrary constant. The method guarantees that the mean and covariance second order accuracy in mean and covariance, giving the same performance as a second order truncated filter but without the need to calculate any Jacobians or Hessians. The impacts of scaling issues are illustrated by considering conversions from polar to Cartesian coordinates with large angular uncertainties.
ISSN:0743-1619
2378-5861
DOI:10.1109/ACC.2002.1025369