Wideband Signal Direction of Arrival Estimation Algorithm for a Single Vector Hydrophone Based on Data Fusion

To enhance the performance of direction of arrival (DOA) estimation for a single vector hydrophone in low-signal-to-noise-ratio (SNR) scenarios, this paper proposes a high-precision algorithm based on data fusion. In low-SNR conditions, because of the influence of noise, the estimation performance of different frequency points in the signal bandwidth differs. In this study, the weights are derived based on the least-mean-square-error criterion, and a novel DOA estimation algorithm is developed by integrating the outcomes from diverse frequency points via a data-fusion methodology. The proposed algorithm integrates data fusion into vector hydrophone processing, which results in better DOA estimation performance than the traditional histogram algorithm. Under the assumption of Gaussian white noise, the simulation results prove the efficacy of the method.