Application of an adaptive extended Kalman filter in SINS/GPS integrated navigation system

For low-cost SINS/GPS integrated navigation system using low precision inertial sensors, the psi-angle model of SINS will degrade the performance of a designed filter due to the neglected error terms in the model. A general SINS error propagation model based on quaternion is presented. The error model is nonlinear and does not rely on small misalignment angles assumption. To estimate SINS errors with uncertain measurement noise, an adaptive extended Kalman filtering method is proposed. In the adaptive filtering method, the components of a measurement vector are processed serially, and the measurement noise covariance matrix is estimated on-line. The simulation results reveal that without exact process and measurement noise covariance matrixes, the adaptive extended Kalman filtering approach can improve the performance of low-cost SINS/GPS integrated navigation system effectively.