DOA Estimation for Low-Angle Targets Using Time–Frequency Deep Learning
Three neural-network-based estimators are developed, including a multilayer perceptron (MLP) that exploits frequency diversity, a bidirectional long short-term memory (BiLSTM) that exploits temporal diversity, and an MLP-BiLSTM fusion network that jointly exploits time and frequency diversity for DOA estimation.