Since the Bit Error Rate (BER) of the Blind Source Separation (BSS) of mixed digital modulation signals under the noisy environment is excessively high, a two-stage blind source separation algorithm named R-TSBS was proposed based on RobustICA (Robust Independent Component Analysis). Firstly, the algorithm used RobustICA to estimate the mixing matrix consisting of array response vector. In the second phase, each symbol sequence transmitted by digital modulation source signal was estimated by Maximum Likelihood Estimation (MLE) method using the finite symbol values character. Finally, R-TSBS achieved the purpose of blind source separation. The simulation results show that, when the Signal to Noise Ratio (SNR) is 10 dB, the BER of traditional Independent Component Analysis (ICA) algorithm such as FastICA (Fast Independent Component Analysis) and RobustICA reached 3.5×10^-2, which is exactly high. However, the BER of the two-stage blind source separation on the basis of FastICA algorithm which named F-TSBS and the proposed R-TSBS algorithm dropped to 10^-3, the separation performance has been significantly improved. At the same time, R-TSBS algorithm can obtain about 2 dB performance increase in low SNR (0~4 dB) compared to F-TSBS algorithm.