Add to ORKGIncludes bibliographical reference.viii, 149 leaves : ill. ; 30 cm.This study is concerned with filters that are robust to uncertainties in either the signal models or the noise statistics. Extensions to an interpolation approach to solving a continuous-time, linear, stationary filtering problem are presented. A robust extended Kalman filter is developed.Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1996
Using results from the field of robust statistics, we derive a class of Kalman filters that are robu...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
This monograph provides the reader with a systematic treatment of robust filter design, a key issue ...
Abstract—We consider filter design of a linear system with parameter uncertainty. In contrast to the...
Kalman filter is one of the best filter utilized as a part of the state estimation taking into accou...
In this paper the robustness of Kalman filtering against uncertainties in process and measurement no...
This report presents a review of recent non-linear and robust filtering results for stochastic syste...
We present some optimality results for robust Kalman filtering. To this end, we introduce the genera...
The Kalman filter (KF) is an extremely powerful and versatile tool for signal processing that has be...
This paper proposes a new robust Kalman filter algorithm under outliers and system uncertainties. Th...
Kalman filter (KF), which is an algorithm that is utilized to estimate unknown variables based on no...
Abstract—In this correspondence paper, a novel robust extended Kalman filter (REKF) for discrete-tim...
Kalman filter is one of the best filter used in the state estimation based on optimality criteria us...
We take up optimality results for robust Kalman filtering from Ruckdeschel (2001, 2010) where robust...
Using results from the field of robust statistics, we derive a class of Kalman filters that are robu...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...
This monograph provides the reader with a systematic treatment of robust filter design, a key issue ...
Abstract—We consider filter design of a linear system with parameter uncertainty. In contrast to the...
Kalman filter is one of the best filter utilized as a part of the state estimation taking into accou...
In this paper the robustness of Kalman filtering against uncertainties in process and measurement no...
This report presents a review of recent non-linear and robust filtering results for stochastic syste...
We present some optimality results for robust Kalman filtering. To this end, we introduce the genera...
The Kalman filter (KF) is an extremely powerful and versatile tool for signal processing that has be...
This paper proposes a new robust Kalman filter algorithm under outliers and system uncertainties. Th...
Kalman filter (KF), which is an algorithm that is utilized to estimate unknown variables based on no...
Abstract—In this correspondence paper, a novel robust extended Kalman filter (REKF) for discrete-tim...
Kalman filter is one of the best filter used in the state estimation based on optimality criteria us...
We take up optimality results for robust Kalman filtering from Ruckdeschel (2001, 2010) where robust...
Using results from the field of robust statistics, we derive a class of Kalman filters that are robu...
This new edition presents a thorough discussion of the mathematical theory and computational schemes...
The Kalman filter is the general solution to the recursive, minimised mean square estimation problem...