In fifth-generation (5G) wireless communications, large-scale arrays pose a challenge to the accuracy of signal models based on the plane wavefront. In this paper, a novel method for 3D near-field direction of arrival (DOA) estimation is proposed based on large-scale uniform rectangular array (URA). First, the near-field signal model based on the vertical rectangular array and the delay phase shift of the received array is presented. Afterwards, the proposed method divides the complete parameters set into multiple-parameters subsets, and only estimates one of them in each iteration, leaving the others in the fixed subset. As a result, we can obtain the maximum convergence rate of the deterministic maximum likelihood (DML) algorithm. Finally, the simulation results demonstrate that the root mean square errors (RMSEs) of the proposed algorithm are closer to the Cramer-Rao lower bounds and converge faster than those of the DML algorithm, confirming its effectiveness and superiority.