The generalized inverse beamforming has attracted wide alttention due to its high spatial resolution and strong sidelobesuppression eapabiliies. To improve the sound souree identifieation performance of GIB, a regularized beamforming method via elasticnet is proposed, which ean ensure the robustness and sparsity of the sound souree identification results, However, the ineoherent noisegenerated in the proeess of measuring the sound source signal may produces unavoidable errors. To suppress the interference noise in themeasurement process, a generalized inverse beamforming method with improved elastie net regularization is proposed by combiningdiagonal denoising with improved eigenvalue method to reconstruct the regularization parameters of beamforming, which could distinguishthe interference noise from the target sound source. Numerical simulation and experimental results both prove that the main lobe widtherror of the proposed algorithm is less than 10 dB at high frequencies, and it has higher spatial resolution and robustness, and strongsidelobe attemuation ability than elastie net regularized heamforming as well.