Robust MP-augmented ukf algorithm in integrated navigation system

Based on the researches of the advantages and disadvantages for model prediction filter, robust filter and unscented Kalman filter, a new robust model predictive-augmented UKF algorithm is proposed. And the input of the system state information is increased by add the drive noise into the system states. The model error is restrained by model predictive filter, and the robustness of the system is enhanced by robust estimation, overcoming the deficiency that the unscented Kalman filter is more sensitive to system model errors. The proposed new algorithm is applied to the SINS/CNS/SAR integrated navigation system for simulation, and the results show that the algorithm can effectively restrain attitude angle error and velocity error, and the convergence rate and accuracy of the filter is superior to the unscented Kalman filter.