Iterative DOA Estimation and MVDR Beamforming for Enhanced SNR in Narrowband Signals

In this study, we propose an iterative direction of arrival (DOA) estimation method combined with minimum variance distortionless response (MVDR) beamforming to enhance the signal-to-noise ratio (SNR) of narrowband signals. A uniform linear array (ULA) of isotropic antennas is employed to collect narrowband signals in a simulated environment with additive white Gaussian noise (AWGN). The multiple signal classification (MUSIC) algorithm is utilized for DOA estimation, and the estimated directions are iteratively refined to align the beamformer with the actual signal direction [1]. This iterative approach mitigates the self-nulling issue commonly observed in MVDR beamformers under directional mismatch conditions. The proposed method demonstrates a significant SNR improvement of 10.61 dB compared to the initial signal condition. Through simulations, we show the effectiveness of the iterative DOA adaptation in reducing noise interference and aligning the beam pattern with the desired signal direction. The results indicate that the combination of iterative DOA estimation and MVDR beamforming is a robust solution for improving narrowband signal quality, particularly in low-SNR environments.