In many speech applications, the essential core problem of signal processing is extracting the desired target speaker from the noisy mixture, which contains the original speech components and background noise, third - party talker, interferences and non- directional noise sources. Speech enhancement method, which utilizes the spatial information about geometry, the direction of arrival (DoA) of an interesting signal, the characteristics of the surrounding environment to achieve noise suppression and speech enhancement at the same time. The microphone array (MA) beamforming has attracted the attention of scholars, researchers and engineering to develop multi-channel signal processing algorithms, especially in acoustical instruments, hearing aids, cochlear implant, mobile phone, teleconference system, surveillance devices and smart home. Minimum Variance Distortionless Response (MVDR) beamformer is an efficient solution for extracting the desired target speaker at a specified direction while minimizing the total output noise power at the output signal of the beamformer. However, in real-life cases, MVDR beamformer’s performance is often corrupted, due to the displacement of MA distribution, the error of sampling frequency and the preferred DoA, the tolerance of MA amplitudes or the difference of microphone sensitivities. In this contribution, the author proposed applying an additive gain function to improve the overall MVDR’s evaluation in real-life environments. The demonstrated experiment confirmed the effectiveness of the author’s suggested technique in reducing the speech distortion to 5.0 dB, enhancing the speech quality in the term of signal-to-noise (SNR) ratio from 10.1 to 10.7 dB. The capability of improving MVDR’s performance has shown that the author’s proposed method can be integrated into a multi-channel system for solving more complicated problems.