Adaptive Extended Kalman filtering Algorithm for SINS/GPS Integrated Navigation in guided munitions

The Integrated Navigation Kalman Filter of Strapdown Inertial Navigation System/Global Positioning System (SINS/GPS) with pesudorange and quaternion as observation information, has been researched for space autonomous navigation. To improve the real-time working performance, an improved Adaptive Extended Kalman filtering algorithm (AEKF) is proposed here to estimate the measurement noise on-line for the SINS/GPS integrated navigation systems. The measurement remnant chi-square method is used to automatically adjust the sliding window basing on the innovation sequence. The experiment result shows that this new approach could improve the accuracy of the integrated navigation system effectively when the measurement noise is unknown. Compared to the original algorithm in longitude, latitude, altitude and velocity, the orientation precision is improved greatly.