Abstract
The acoustic vector sensor is a complete acoustic field measurement device and is widely used in underwater direction-of-arrival (DOA) estimation. The maximum likelihood (ML) estimator is optimal for two-dimensional DOA estimation. However, it requires prior knowledge of noise variances, which is not always available. Sometimes we pay more attention to DOA on the horizontal plane in applications such as remote localization, cases where vertical interference is present. To investigate the performance of ML estimator in such a one-dimensional DOA estimation problem, we make a comparison between ML estimator and several DOA estimation techniques under a framework of weighted beamforming. Performances of these estimators are evaluated by the approximate mean square error. Simulation results show that there is no significant performance difference between the CBF beamformer and the ML estimator within a moderate range of the ratio of acoustic pressure noise power to particle velocity noise power.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
