DocumentCode
2038699
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
fYear
2009
fDate
23-24 May 2009
Firstpage
1
Lastpage
4
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/IWISA.2009.5072908
Filename
5072908
Link To Document