Surface mass anomalies estimated by mass concentration (mascon) approach using Gravity Recovery and Climate Experiment (GRACE) observations with regularization constraints generally present higher spatial resolution than the spheric harmonic (SH) solutions. To analyze the influence of different types of constraints on the estimation of mascon solutions, we carried out a closed-loop simulation experiment to estimate surface mass anomalies over South America based on simulated GRACE intersatellite geopotential differences. Tikhonov regularization with spatial constraint (SC), uniform weighting constraint (UWC), and a prior information constraint (APC) were employed to stabilize the mascon solutions, and the corresponding optimal regularization parameters were determined based on the minimum residual root-mean-square (RMS) criterion. The results show that mascon solutions estimated under different types of constraints are consistent and equivalent when the optimal regularization parameters are selected. The spatial distributions and main characteristics of regional surface mass anomalies estimated by the three types of constraints agree well, and the values of residual RMS with different constraints are very close. But due to the smoothing effect of regularization, the signal strength of mascon solutions is a bit weaker than that of original true signal, especially in the regions with strong signals. In addition, due to the ill-conditioned problem is more serious for higher grid resolution, the relative contribution of the three types of constraints to the final mascon solutions would be stronger. The results show that the averages of relative contribution percentages of these constraints for 2°×2° mascon grids are 80% -90%, while the corresponding values for 4°×4° mascon grids are 30% -60%. However, based on the minimum residual RMS criterion, the accuracy of estimation results is not affected by the type of constraints and their relative contribution to the final mascon solutions.