The theoretic foundation of traditional microphone array postfilters is the signal model in which the noise between sensors is assumed to be uncorrelated. However, this model is inaccurate in real environments since the correlated noise exists. In this paper, a more generalized signal model which considers both the correlated and uncorrelated noise is introduced. A general expression of the microphone array post-filter is proposed for this model. For better residual noise shaping, the human auditory property is incorporated into the post-filter estimation process. In experiments with real noise microphone array recordings, the proposed technique has shown to produce impressive results in terms of quality measures of the enhanced speech.