Abstract: For some regular microphone arrays, the Kronecker product (KP) decomposition can be used to improve the robustness of the minimum variance distortionless response (MVDR) beamformer, as well as to reduce its computational complexity. When the number of microphones becomes large, the Kronecker product decomposition may lose effectiveness due to increased possibility of microphones damage. In this paper, three different categories of microphone invalidations are studied and their impacts on the performance of the MVDR and the Kronecker product-based adaptive beamformers are analyzed. Simulation and experimental results show that the microphone channels completely missing signals have the greatest impact on beamformers, while the microphone channels with duplicated signals have the least impact. According to these results, a low-complexity signal recovery method is proposed, which uses the signal of adjacent channel to replace the signal missing channels to improve beamforming performance in the case of microphones invalidation.