Title :
A cubature Kalman filter with uncompensated biases
Author :
Xia Ning ; Jian Yang
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
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;
Conference_Titel :
Image and Signal Processing (CISP), 2013 6th International Congress on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4799-2763-0
DOI :
10.1109/CISP.2013.6745229