Nonlinear algorithm based on UKF for low-cost SINS/GPS integrated navigation system

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. This paper establishes nonlinear mathematics model based on quaternion error equations. For essential nonlinear systems, the unscented Kalman filter (UKF) has some advantages such as high estimation precision, fast convergence, and so on. In order to deal with the problem that the inertial sensors errors can not be estimated using UKF method, an improved algorithm combining UKF and extended Kalman filters is proposed. The simulation results show that this method has better precision of all misalignment angles especially the azimuth one than that of extended Kalman filters.