UCL logo

UCL Discovery

UCL home » Library Services » Electronic resources » UCL Discovery

A new method for the nonlinear transformation of means and covariances in filters and estimators

Julier, S; Uhlmann, J; Durrant-Whyte, HF; (2000) A new method for the nonlinear transformation of means and covariances in filters and estimators. IEEE T AUTOMAT CONTR , 45 (3) 477 - 482.

Full text not available from this repository.

Abstract

This paper describes a new approach for generalizing the Kalman filter to nonlinear systems. A set of samples are used to parameterize the mean and covariance of a (not necessarily Gaussian) probability distribution. The method yields a filter that is more accurate than an extended Kalman filter (EKF) and easier to implement than an EKF or a Gauss second-order filter. Its effectiveness is demonstrated using an example.

Type: Article
Title: A new method for the nonlinear transformation of means and covariances in filters and estimators
Keywords: covariance matrices, estimation, filtering, missile detection and tracking, mobile robots, nonlinear filters, prediction methods, TARGET TRACKING
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/153473
Downloads since deposit
0Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item