Direction-of-arrival estimation for weak underwater targets via flexible sparsity-aware modeling

Direction-of-arrival (DOA) estimation plays a critical role in underwater acoustic applications such as target detection, localization, tracking, and identification. Unlike image or speech processing, underwater array signal processing faces unique challenges because of low signal-to-noise ratio (SNR) and limited snapshots. In such conditions, whether traditional methods (e.g., conventional beamforming, multiple signal classification) or learning-based approaches (e.g., sparse Bayesian learning)