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.
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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.
|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 > Computer Science|
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