Title :
Nonlinear algorithm based on new Kalmanfiltering method for integrated SINS / GPS Navigation System
Author :
Bin, Li ; Qing, Xiao Ming
Author_Institution :
Eng. Coll., Air Force Eng. Univ., Xi´´an, China
Abstract :
Aimed at a low-cost scheme of SINS/GPS integrated navigation system using low precision inertial sensors (MIMU), the precise error equations is basic for filter. The psi-angle model has been widely used. However, the model is not effective for a system with large attitude errors because the neglected error terms in the model degrade the performance of a designed filter. Different correcting methods of Kalman filter for deep integration of pseudorange with strapdown inertial navigation system are investigated in this paper. On the base of analyzing navigation errors, a composed correcting Kalman filter for SINS/GPS integrated navigation system is proposed by combining output correcting method and feedback correcting method. Compared with the two correcting methods, the composed correcting method improves the integration system navigation accuracy. The simulation results show the efficiency of this composed correcting Kalman filter.
Keywords :
Global Positioning System; Kalman filters; inertial navigation; Kalman filtering; attitude errors; feedback correcting method; integrated SINS/GPS navigation system; low precision inertial sensors; nonlinear algorithm; precise error equations; psi-angle model; strapdown inertial navigation; Degradation; Error analysis; Error correction; Filters; Global Positioning System; Inertial navigation; Nonlinear equations; Output feedback; Sensor systems; Silicon compounds; integrated navigation; navigation error; nonlinear;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5358351
