The unscented Kalman filtering in extended noise environments
Authors:
- 1 January 2009
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 07431619,p. 1865-1870
Abstract
This paper introduces an extended environment for the unscented Kalman filtering that considers also the presence of additive noise on input observations in order to solve the problem of optimal estimation of noise-corrupted input and output sequences. This environment includes as sub-cases both errors-in-variables filtering and unscented Kalman filtering. The unscented Kalman filtering to the presence of additive noise on input observations is considered, and is used to solve the problem of optimal estimation of noise-corrupted input and output sequences. A Monte Carlo simulation shows that the performance of the unscented Kalman filtering technique leads to the expected minimal variance estimates.Keywords
This publication has 18 references indexed in Scilit:
- Kalman filtering in extended noise environmentsIEEE Transactions on Automatic Control, 2005
- Performance bounds and comparison of nonlinear filters for tracking a ballistic object on re-entryIEE Proceedings - Radar, Sonar and Navigation, 2003
- Optimal errors-in-variables filteringAutomatica, 2003
- Algorithms for optimal errors-in-variables filteringSystems & Control Letters, 2003
- The unscented Kalman filter for nonlinear estimation2002
- Comment on "A new method for the nonlinear transformation of means and covariances in filters and estimators" [with authors' reply]IEEE Transactions on Automatic Control, 2002
- The scaled unscented transformation2002
- A new method for the nonlinear transformation of means and covariances in filters and estimatorsIEEE Transactions on Automatic Control, 2000
- An extended Kalman filter frequency tracker for high-noise environmentsIEEE Transactions on Signal Processing, 1996
- Global total least squares modeling of multivariable time seriesIEEE Transactions on Automatic Control, 1995