Under the criterion of maximum output signal-to-noise ratio （SNR）， the problem of difficult control of complex-valued coefficients in generalized eigenvalue （GEV） beamforming is encountered， and severe distortion of the output signal can be caused in complex acoustic environments. To address the issue of complex-valued coefficient estimation， a complex-valued coefficient estimation method based on minimum mean square error （MMSE） is proposed in this paper. By introducing a speech distortion weight factor （SDW）， the weight relationship between noise reduction and speech distortion is adjusted， thereby proposing a method for generalized eigenvalue robust beamforming based on SDW-MMSE. The power spectra of the target and noise signals are estimated using maximum likelihood method， and the main generalized eigenvectors are then determined. Furthermore， the complex-valued coefficients are estimated ， and the complex coefficients are combined with the principal generalized eigenvector to obtain the generalized eigenvalue robust beamforming filter vector based on SDW-MMSE. Through simulation experiments， it is demonstrated that the proposed beamforming method effectively eliminates coherent and incoherent noise， and exhibits robust performance with high output SNR and low speech distortion.