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To solve the problem that the ship’s strapdown inertial navigation system (SINS) alignment accuracy decreases with the increase of the nonlinear filtering state dimension under mooring conditions, a method based on Kalman filter (KF) and Adaptive scale mini-skewness single line sampling Unscented Kalman Filter (ASMUKF) hybrid filtering algorithm is...
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Random angular motion and instantaneous linear motion are the main interference sources to the coarse alignment of strapdown inertial navigation system (SINS) in mooring state. To weaken the influence of heave motion on coarse alignment, a weighted observation vectors method is proposed according to wave mechanics. After extracting the heave motion trajectory roughly, the motion state of water particle in different phases is retrieved according to the measured motion parameters combined with small amplitude wave theory, and the weight distribution of the observed vectors is determined by the acceleration law of water particles in the
${z}$
-axis direction. It ensures that the observed vectors in a relatively stable state are assigned higher weights, while the vectors in other states with a rapid change of attitude lower weights. Finally, we designed filed experiments and conducted comparative studies on the proposed method and the traditional coarse alignment methods based on apparent gravitational motion (AGM), apparent velocity motion (AVM), and sliding fixed-interval integration (SFI), respectively. The results show that the vector weighting method can widely and effectively improve the accuracy of coarse alignment in yaw with the contribution to reducing the interference of waves on mooring alignment.
