Abstract In order to solve the problem of abnormal disturbance of dynamic model and gross error of gravity anomaly observation data in SITAN algorithm for underwater gravity matching navigation, we propose a robust adaptive matching algorithm. We construct the adaptive factor and the robust factor to adjust the weight of the contribution of state prediction information and measurement information to the filtering, which can effectively suppress the influence of gross error and prediction information anomaly, and improve the stability and reliability of the matching algorithm. In the South China Sea, a sea area with rich variation of gravity anomaly features is selected for simulation experiments. The results show that compared with the ordinary SITAN algorithm, the proposed algorithm can significantly reduce the influence of abnormal observations, and the positioning accuracy and robustness of the system are improved.