DOA estimation of the moving targets in shallow water based on vector optimization beamforming and normal-mode theory
DOA estimation is one of the most important tasks for sonar system. However, the performance of conventional high-resolution DOA estimation methods is influenced because of the neglect of some important factors, such as effect of underwater sound channel, the array position errors and so on. In order to improve the robustness of the high-resolution DOA estimation methods, the vector optimization robust beamforming method is realized by adding a strong joint constraint to the weight vector norm and the steering vector errors. In addition, simulating the matched-field processing method, the DOA estimation of underwater moving targets can be computed by combining adaptive robust beamforming and normal-mode theory. It is shown that the adaptive beamforming which is presented in this paper has higher peak to maximum sidelobe ratio (PSR) and narrower ~3dB beamwidth.