<p>After parts of the antennas are damaged, partial data loss could occur in the received signal and be impacted by colored noise during transmission at the receiving end. These problems would affect the direction of arrival (DOA) estimation performance. To achieve higher-performance DOA estimation, this paper proposes an efficient approach for DOA estimation based on robust principal component analysis (RPCA). To begin with, the acquired array signal is whitened to mitigate the effects of colored noise on the array received signal. Then, the problem of recovering the array received signal is formulated as a low-rank matrix restoration problem based on RPCA, and the array received signal’s time-domain smoothing information is introduced to further suppress the residual noise in the recovered signal. Secondly, the Schatten-p norm is added to the RPCA model to realize the proportion of the large singular value corresponding to the weakened target signal in the process of kernel norm optimization in the RPCA model, so as to get closer to the purpose of restoring the rank minimization of the low-rank matrix. In addition, the weighted Schatten-p norm would strengthen the characteristic, so as to obtain the low-rank characteristic information closer to the desired signal. In the end, to estimate the arrival angle of the recovered array signal, the traditional DOA estimation algorithm is employed. Simulation results show that the proposed algorithm achieves higher target signal gain and lower angle estimation error than other related low-rank matrix recovery DOA estimation algorithms in complex noise environments.</p>