DOA Estimation of Underwater Acoustic Targets Based on Bayesian Compressed Sensing
Fei Liu · Journal of Physics Conference Series · 2022
Abstract Aiming at the performance degradation or even failure of existing underwater acoustic target direction of arrial (DOA) estimation methods under the conditions of low signal-to-noise ratio and low snapshot, a underwater acoustic target DOA estimation method based on sparse Bayesian compressed sensing theory is studied, and simulation experiments are carried out by MATLAB to verify the feasibility and effectiveness of the proposed method. Simulation results show that compared with CBF , MUSIC and OMP algorithms, the proposed method can improve the estimation accuracy in the case of lower snapshot number, lower number of array elements and smaller array element spacing, and can achieve high resolution DOA estimation in the case of low signal-to-noise ratio and close position of multiple target signals.