Abstract
This paper presents a modified Sage‐Husa adaptive Kalman filter‐based SINS/DVL integrated navigation system for the autonomous underwater vehicle (AUV), where DVL is employed to correct the navigation errors of SINS that accumulate over time. When negative definite items are large enough, different from the positive definiteness of noise matrices which cannot be guaranteed for the conventional Sage‐Husa adaptive Kalman filter, the proposed modified Sage‐Husa adaptive Kalman filter deletes the negative definite items of adaptive update laws of the noise matrix to ensure the convergence of the Sage‐Husa adaptive Kalman filter. In other words, this method sacrifices some filtering precision to ensure the stability of the filter. The simulation tests are implemented to verify that expected navigation accuracy for AUV can be obtained using the proposed modified Sage‐Husa adaptive Kalman filter.
Highlights
Autonomous underwater vehicle (AUV) has been widely used in ocean exploration, where accurate navigation and positioning ability are essential to ensure the long voyage operation of AUV
Since the strapdown inertial navigation (SINS) is with the advantages of strong autonomy, high precision, and full navigation parameters, it is widely used in the navigation system of AUV
The navigation error of SINS is accumulated over time, which results in low navigation accuracy
Summary
Autonomous underwater vehicle (AUV) has been widely used in ocean exploration, where accurate navigation and positioning ability are essential to ensure the long voyage operation of AUV. Since the Kalman filter is able to estimate the system states in the presence of noises, it is widely applied in the SINS/DVL integrated navigation system. The inaccurate measurement model under the time-varying measurement noise results in substantial estimation errors or even filter divergence To solve this problem, the interacting multiple model algorithm which uses more than one model is proposed in [11], where a variable model set based on the model. A modified Sage-Husa adaptive Kalman filter-based SINS/DVL integrated navigation system is proposed to provide the AUV with accurate navigation parameters, where the adaptive update laws of the noise matrix are modified by deleting the negative definite items.
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