DocumentCode
3355583
Title
A cubature Kalman filter with uncompensated biases
Author
Xia Ning ; Jian Yang
Author_Institution
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Volume
2
fYear
2013
fDate
16-18 Dec. 2013
Firstpage
1148
Lastpage
1152
Abstract
An improved nonlinear filter is proposed in the framework of the cubature Kalman filter (CKF) with uncompensated biases. This filter can be applied for the nonlinear system with unknown random biases, which are unable to be modeled in practical situations. The proposed method can decrease the state estimation error and demonstrate the excellent numerical stability in the process of the filtering. The performance is verified by Matlab simulations in the context of the radar tracking.
Keywords
Kalman filters; radar tracking; state estimation; CKF; Matlab simulations; cubature Kalman filter; improved nonlinear filter; numerical stability; radar tracking; state estimation error; uncompensated biases; Bayes methods; Kalman filters; Mathematical model; Noise; Noise measurement; Vectors; cubature Kalman filter; nonlinear filter; radar tracking; uncompensated biases;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location
Hangzhou
Print_ISBN
978-1-4799-2763-0
Type
conf
DOI
10.1109/CISP.2013.6745229
Filename
6745229
Link To Document