[Objective]To address the problem of ultra-short baseline(USBL)relative navigation and posi-tioning during the dynamic docking of an autonomous underwater vehicle(AUV)in shallow water,a com-pensated unscented particle filter(CUPF)algorithm based on a disturbance observer is proposed.[Methods]The CUPF algorithm compensates for missing values in the USBL data based on the dead reck-oning model,estimates the unknown disturbances in the dynamic docking of the AUV using observer techno-logy and filters outliers in the USBL data combined with the unscented particle filter to realize the estimation of the AUV's state.[Results]The lake trial data shows that the proposed CUPF algorithm can effectively remove outliers and fill in missing values for USBL positioning with a speed estimation error of less than 15%and computation time reduced by 57%compared with traditional methods.[Conclusions]The CUPF al-gorithm can improve the positioning accuracy of USBL while smoothing the AUV motion trajectory and state estimation by fully utilizing relative measurement information for AUV docking.
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