DocumentCode :
3526351
Title :
Building nonlinear filter toolbox with scilab
Author :
Xu, Tao ; Ma, Longhua
Author_Institution :
Instn. of Navig. Guidance & Control, Zhejiang Univ., Hangzhou, China
fYear :
2009
fDate :
18-20 Sept. 2009
Firstpage :
163
Lastpage :
168
Abstract :
Nowadays nonlinear theories and nonlinear filtering technology are becoming more and more popular, especially in the fields of navigation guidance and control, image processing, malfunction detecting and objective tracking and so on. The most commonly used nonlinear filter algorithms are EKF (extended Kalman filter) and UKF (unscented Kalman filter) which are both under the limitation of Gauss distribution condition. While in recently, PF (particle filter) turns up with no limitation of Gauss distribution condition. In this paper, we will build a nonlinear filter toolbox on the base of Scilab computing software, including EKF, UKF and PF functions. The paper also gives two applications in nonlinear filter fields and the results show the toolbox is available.
Keywords :
Gaussian distribution; Kalman filters; nonlinear filters; particle filtering (numerical methods); Gauss distribution condition; Scilab computing software; extended Kalman filter; image processing; malfunction detecting; navigation guidance and control; nonlinear filter algorithms; nonlinear filter toolbox; nonlinear filtering technology; nonlinear theory; objective tracking; particle filter; unscented Kalman filter; Density functional theory; Filtering algorithms; Gaussian distribution; Gaussian processes; Image processing; Navigation; Nonlinear filters; Particle filters; Software algorithms; Software tools; Nonlinear Filter; Scilab software; Toolbox;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Open-source Software for Scientific Computation (OSSC), 2009 IEEE International Workshop on
Conference_Location :
Guiyang
Print_ISBN :
978-1-4244-4452-6
Electronic_ISBN :
978-1-4244-4453-3
Type :
conf
DOI :
10.1109/OSSC.2009.5416912
Filename :
5416912
Link To Document :
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