A Novel DVL-Aided SINS Coarse Alignment Method Under Non-Mooring Condition

When performing the dual-vector attitude decomposition-based initial alignment (DVA) in offshore environments, an unmoored vehicle is susceptible to disturbances from wave and ocean current. These disturbances can induce vehicle disturbance acceleration, which distorts the gravitational vector measured by the SINS and ultimately lead to attitude error. To address this issue, a novel DVL-aided coarse alignment method is proposed, which mitigates the observation vector errors introduced by vehicle acceleration in two ways: 1) Replacing the original integration interval. By using SINS data, the observation vector is constructed by selecting the data segment corresponding to the window with the minimum average resultant disturbance acceleration through a sliding window.2) Compensating the accelerometer output. The disturbance acceleration is reduced by compensating for it using the DVL. The effectiveness of the new method was verified using lake trial in both moored and unmoored conditions. Compared with the traditional method, the proposed method shows improved robustness and accuracy. In cases where the vehicle exhibits significant linear motion during the coarse alignment stage, the proposed method effectively reduces the gravitational acceleration vector deviation caused by vehicle acceleration. the positioning error obtained through SINS/DVL dead reckoning using the initial attitude information provided by the proposed method is significantly reduced compared to the conventional method. The statistical analysis of positioning errors across the different voyages, indicates that the proposed method significantly improves positioning accuracy by a maximum of 97.4% and a minimum of 5.9% compared to the original method.