Title :
Kalman and smooth variable structure filters for robust estimation
Author :
Gadsden, Stephen Andrew ; Habibi, Saeid ; Kirubarajan, Thia
Author_Institution :
Mech. Eng., McMaster Univ., Hamilton, ON, Canada
Abstract :
The extended Kalman filter (EKF) and the unscented Kalman filter (UKF) are among the most popular estimation methods. The smooth variable structure filter (SVSF) is a relatively new sliding mode estimator. In an effort to use the accuracy of the EKF and the UKF and the robustness of the SVSF, the filters have been combined, resulting in two new estimation strategies, called the EK-SVSF and the UK-SVSF, respectively. The algorithms were validated by testing them on a well-known target tracking computer experiment.
Keywords :
Kalman filters; estimation theory; nonlinear filters; target tracking; variable structure systems; EKF; SVSF; UKF; extended Kalman filter; robust estimation; sliding mode estimator; smooth variable structure filters; target tracking; unscented Kalman filter; Equations; Estimation; Kalman filters; Mathematical model; Nonlinear systems; Robustness; Smoothing methods;
Journal_Title :
Aerospace and Electronic Systems, IEEE Transactions on
DOI :
10.1109/TAES.2014.110768