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Recently, direction-of-arrival (DOA) and position estimation for acoustic signals has been studied intensively and many different algorithms have been proposed. Among different solutions for multiple sources, blind source separation (BSS) methods have drawn much attention due to their good performance. In this paper, we present a localization algorithm using the results from a frequency domain independent component analysis (ICA) algorithm combined with an extended version of the state coherence transform (SCT). We motivate the SCT as an approximated maximum likelihood (ML) approach and compare our localization algorithm with the steered-response power with phase transform (SRP-PHAT) and the averaged directivity pattern (BSS-ADP) algorithm. 2D localization results show superior performance of our algorithm.