Abstract-Clutter suppression and ground moving target indication(GMTI) are pressing tasks in multichannel synthetic aperture radar (SAR) system. In recent years, sparse representation, the theory of robust principal component analysis (RPCA) has made significant progress. In this paper, we propose a fast along-track interferometry (ATI)-RPCA based moving target detection method in multichannel SAR system(MSAR) to utilize its prominent performance in distinguishing the different parts from a set of correlative database even with channel unbalance or platform motion error. As we all know, space-time adaptive processing (STAP) method would have a bad performance when the training samples are contaminated by moving targets. Subsequently, we apply the ATI-RPCA based method in the range-Doppler domain to separate the moving targets in order to improve the performance of STAP. Since the moving targets can be separated through RPCA, the remaining samples, which can be considered as only clutter, can be used to estimate the covariance matrix accurately for further processing. Most of all, the ATI-RPCA method only takes several iterations to reach the convergence compared to traditional RPCA.