DocumentCode :
638882
Title :
Strong tracking cubature Kalman filter algorithm for GPS/INS Integrated Navigation System
Author :
Qiurong Li ; Feng Sun
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear :
2013
fDate :
4-7 Aug. 2013
Firstpage :
1113
Lastpage :
1117
Abstract :
The GPS/INS Integrated Navigation System is nonlinear in nature. To deal with the accuracy of GPS/INS navigation under nonlinear, strong tracking cubature Kalman flter (STCKF) is applied to the system. The heart of the CKF is a cubature rule, which makes it possible to numerically compute multivariate moment integrals encountered in the nonlinear Bayesian filter. STCKF is presented for simulation. Simulation results show the superior performance of this approach when compared with clasaical suboptimal techniques such as extended Kalman filter (EKF). The results of simulation demonstrate the improved performance of the STCKF over conventional nonlinear filters. The research provides theoretical support for engineering design and modification. STCKF has the advantages of high reliability, low sensitivity, strong robustness, strong stability and convergence.
Keywords :
Bayes methods; Global Positioning System; Kalman filters; inertial navigation; nonlinear filters; numerical analysis; reliability; stability; tracking filters; EKF; GPS-INS integrated navigation system; STCKF; extended Kalman filter; multivariate moment integral; nonlinear Bayesian filter; reliability; stability; strong tracking cubature Kalman filter algorithm; Global Positioning System; Information filters; Kalman filters; Mathematical model; Nonlinear filters; Cubature Kalman filter(CKF); GPS/INS; Strong tracking(ST); cubature rule;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2013 IEEE International Conference on
Conference_Location :
Takamatsu
Print_ISBN :
978-1-4673-5557-5
Type :
conf
DOI :
10.1109/ICMA.2013.6618070
Filename :
6618070
Link To Document :
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