Multiple Model Adaptive Estimation Algorithm for SINS/CNS Integrated Navigation System

Abstract

In this paper, a new filtering method based on multiple model adaptive estimation(MMAE) algorithm is proposed, for the problem of poor adaptability of single model filters with unknown or uncertain parameters. In this proposed algorithm, we use improved Kalman filters rather than traditional Kalman filters, such as extended Kalman filter (EKF), unscented Kalman filter (UKF). And EKF and UKF are used as sub filters in MMAE algorithm to realize the state estimation of nonlinear system. Meanwhile, this method is applied to the SINS/CNS integrated navigation system under the motion of ballistic missile. As the simulation result shows, the improved filtering methods have better navigation accuracy, and can solve the problem of poor adaptability of single model filter, when compared with traditional EKF and UKF algorithms.

Keywords

multiple model adaptive estimation / Kalman filter / strap-down inertial navigation / celestial navigation / integrated navigation

References

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