Variations of Unscented Kalman filter with their applications in target tracking on re-entry

Author

Shu-Chun Zhang ; Guang-Da Hu

Author_Institution

Harbin Inst. of Technol., China

fYear

2006

fDate

7-11 Aug. 2006

Firstpage

407

Lastpage

412

Abstract

The most usually used method in nonlinear filtering and tracking community is extended Kalman filter. To make filtering results more accurate while keeping comparable complexity with those of real-time filters, the idea of iteration can be considered in the process of updating. In this paper new iterative methods using unscented transform are presented. An application in target tracking on re-entry shows their performance advantages. In addition, square root UKF is included in the simulation as another variation of UKF to improve statistical performance.

Keywords

Kalman filters; iterative methods; nonlinear filters; object detection; statistical analysis; target tracking; transforms; iterative methods; nonlinear filtering; reentry; square root filtering; statistical performance; target tracking; unscented Kalman filter; unscented transform; Covariance matrix; Differential equations; Electronic mail; Filtering; Iterative algorithms; Iterative methods; Kalman filters; Nonlinear equations; State estimation; Target tracking; Iteration; Nonlinear filtering; Square root filtering; Tracking; Unscented Transform;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2006. CCC 2006. Chinese

Conference_Location

Harbin

Print_ISBN

7-81077-802-1

Type

conf

DOI

10.1109/CHICC.2006.280583

Filename

4060546