The application discloses a kind of robust
direction of arrival estimation method based on ADMM-Net, by expanding ADMM
algorithm into model-driven deep network ADMM-Net to improve DOA
estimation accuracy, speed up DOA
estimation speed and have robustness to array disturbance.Firstly, the sparse transformation of source and array received multi-shot data is carried out by space over-complete dictionary, and the DOA estimation is converted into
compressed sensing sparse
recovery problem;Then, ADMM
algorithm is expanded, and model-driven deep network ADMM-Net with explainability is formed;ADMM-Net is used to reconstruct source power spectrum and carry out DOA estimation.The present application can learn the hyperparameters in iterative
algorithm and array disturbance, solve the problem that existing
compressed sensing DOA estimation method based on calculation speed is slow, and fails under the condition of array disturbance, realize fast, accurate, explainable and robust DOA estimation.