Abstract
Global navigation satellite system (GNSS) is the most widely used position, navigation and time service system. However, GNSS such as BeiDou Navigation Satellite System (BDS) cannot provide the external assistance information for the autonomous underwater vehicle (AUV) because of the blocking effect of water on electromagnetic wave. The uncertain and non-Gaussian characteristics of the measurement noise may degrade the performance of SINS/DVL integrated navigation under the standard Kalman filter (KF) framework. To solve this problem, this paper proposes a robust interacting multiple model algorithm (IMM-RKF) based on the Mahalanobis distance algorithm. Furthermore, two switching sub-models will depict the uncertain parameters. The contributions of the work presented here are twofold. First, this paper robustifies the IMM algorithm under non Gaussian condition, and second the research method is verified in the problem of SINS/DVL integrated navigation. Simulation experimental results for the problem of SINS/DVL integrated navigation under non-Gaussian and uncertain conditions demonstrate the validity and superiority of the proposed method.
Published Version
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