Title :
GPS/SINS Positioning Method Based on Robust UKF
Author :
Qiuting Wang ; Duo Xiao
Author_Institution :
Dept. of Inf. & Electr. Eng., Zhejiang Univ. City Coll., Hangzhou, China
Abstract :
As an improved Unscented Kalman Filtering (UKF) Algorithm, the robust UKF is proposed to solve the positioning accuracy problem of GPS/SINS integrated navigation system used in dynamic environment. The robust estimation theory is applied to the standard UKF algorithm to solve the estimation-error problem in the satellite integrated navigation system. This problem is mainly caused by observation gross-error and the error model uncertainty. Therefore, this new algorithm introduces equivalent covariance matrix based on M-estimated principle. The state equation and observation equation of the system are established to be the mathematical model. The experimental results indicate that the robust UKF can ensure the quality the observation information, as well as improve the accuracy and reliability of the GPS/SINS positioning solution. Besides, it can also improve the receiver´s location performance at the presence of gross errors.
Keywords :
Global Positioning System; Kalman filters; covariance matrices; estimation theory; inertial navigation; nonlinear filters; reliability; GPS-SINS integrated navigation system; GPS-SINS positioning method; M-estimated principle; equivalent covariance matrix; error model uncertainty; mathematical model; observation equation; observation gross-error; reliability; robust UKF algorithm; robust estimation theory; satellite integrated navigation system; state equation; unscented Kalman filtering algorithm; Equations; Global Positioning System; Kalman filters; Mathematical model; Robustness; Silicon compounds; Standards; GPS/SINS; M-estimated principle; observation gross-error; robust UKF;
Conference_Titel :
Industrial Control and Electronics Engineering (ICICEE), 2012 International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4673-1450-3
DOI :
10.1109/ICICEE.2012.233
