Title :
Improvement of UKF Algorithm and Robustness Study
Author :
Mou Zhong-Kai ; Sui Li-Fen
Author_Institution :
Inst. of Survey & Mapping, Inf. Eng. Univ., Zhengzhou
Abstract :
Iterated unscented Kalman filter (IUKF) algorithm has improved the unscented Kalman filter (UKF) and enhanced the performance of filter estimation by using Newton-Raphson iterative equation. This paper improves IUKF algorithm ulteriorly after detailedly analyzing principle of IUKF and its iterative equation, and proposes a new filtering algorithm with robustness-Improved IUKF. Then the performance of the new algorithm is validated by two experiments. The results show that the improved IUKF is more robust which can effectively resist the influence of measurement outlier.
Keywords :
Kalman filters; Newton-Raphson method; Newton-Raphson iterative equation; UKF algorithm; measurement outlier; unscented Kalman filter; Density measurement; Equations; Filtering algorithms; Filters; Iterative algorithms; Linear approximation; Resists; Robustness; State estimation; Taylor series;
Conference_Titel :
Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-3893-8
Electronic_ISBN :
978-1-4244-3894-5
DOI :
10.1109/IWISA.2009.5072908