The iterated divided difference filter

Author

Shi, Yong ; Han, Chongzhao ; Lian, Feng

Author_Institution

Sch. of Electron. & Inf. Eng., Xian JiaoTong Univ., Xian

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

1799

Lastpage

1802

Abstract

With an application to target tracking, the iterated divided difference filter is presented. In new algorithm, an iterated measurement update was proposed to improve the approximation accuracy of the nonlinear state estimation. When iterating, the current mean and the covariance of the divided difference filter (DDF) were used to measurement update procedure. The simulations show that iterated DDF is capable of providing better performance than the standard DDF, especially in the case of significant nonlinearity in the system function.

Keywords

approximation theory; filtering theory; iterative methods; nonlinear filters; state estimation; target tracking; iterated divided difference filter; iterated measurement update; nonlinear filtering problem; nonlinear state estimation; target tracking; Approximation algorithms; Automation; Information filtering; Information filters; Interpolation; Jacobian matrices; Logistics; State estimation; Target tracking; Taylor series; Iterated filter; Nonlinear estimation; divided difference filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation and Logistics, 2008. ICAL 2008. IEEE International Conference on

Conference_Location

Qingdao

Print_ISBN

978-1-4244-2502-0

Electronic_ISBN

978-1-4244-2503-7

Type

conf

DOI

10.1109/ICAL.2008.4636449

Filename

4636449