High Performance Hybrid Robust Extended Kalman Filter Design with Application to Large Misalignments

In many applications, especially military applications, the inertial navigation system (INS) needs to achieve a high level of accuracy in a short time. For alignment, recursive estimator filters and, in non-linear cases, the Extended Kalman Filter (EKF) is often used. The dynamics of a real, continuous system and the output of the sensors are available discretely. Therefore, a hybrid filter has been used. In addition, a robust filter is used to increase the reliability of system operation. In this paper, a Hybrid Extended Kalman Filter (HEKF) is presented and then upgraded to the Hybrid Robust Extended Kalman Filter (HREKF). By running the algorithm on the data of a real system, it was observed that the speed of convergence increased especially in the yaw direction. By running the algorithm on the data of a real system, it was observed that the speed of convergence has increased especially in the yaw direction. Finally, using the impulsive system approach, a new stability analysis of the proposed algorithms is presented, which guarantees the boundedness of the error estimation, which is unique.