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An Efficient SINS/DVL Integrated Navigation Algorithm Compensating for Motion Effects
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AI
DOI：10.1109/tvt.2026.3745575.png)
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Abstract
En 中文
The strapdown inertial navigation system/Doppler velocity log (SINS/DVL) integrated system facilitates precise underwater navigation for autonomous underwater vehicles (AUVs). However, conventional DVL measurement models assume that the vehicle velocity and beam direction remain unchanged during the acoustic round-trip. This assumption fails when the vehicle undergoes translational motion involving high speed, acceleration, or jerk. The resulting motion-dependent errors degrade the navigation accuracy. To address these limitations, this paper proposes a motion-compensated Doppler shift model within a SINS/DVL framework. First, a state back-projection method is developed to estimate the transmission-instant state from the reception-instant navigation solution, which avoids historical-data buffering. Based on this method, a generalized Doppler shift formula is derived. The formula approaches the classical Doppler model when its motion-dependent corrections are negligible, confirming theoretical consistency. Then, the proposed model is integrated into a tightly coupled SINS/DVL filter as a measurement compensation loop without modification to the filter architecture. Simulations and field tests validate the framework under translation-dominated scenarios with mildly curved trajectories. Field test results demonstrate that the proposed method reduces the horizontal positioning RMSE by 13.4% relative to the conventional method. Compared with buffered state interpolation, the proposed method reduces both state-storage requirements and computation time, providing a practical accuracy-cost trade-off.
Keywords:
SINS/DVL integrated system
motion-dependent errors
generalized Doppler shift formula
buffering-free formulation
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7.1
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1.8W
Citations:
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