Uniformly priorized Bayesian adaptive beamforming method

This paper proposed a uniform prior distribution based Bayesian adaptive beamforming algorithm (UB) for UUV flank array under the presence of the DOA error. The DOA of the desired signal is assumed to be a random variable with a prior uniformly distribution in an interval. By using the received data vectors, which considers the average effect of the DOA error, and the Bayesian posterior distribution, UB can estimate the DOA of the desired signal, subsequently calculate the weight vectors. Simulation results show that the algorithm outperforms other beamforming algorithms with the presence of the desired DOA error. The mainlobe of array beampattern always aligned with the direction of the arrival signal. The output signal to inference noise ratio (SINR) increases steadily with the input signal to inference noise ratio (SNR) and the number of snapshots. Simultaneously, it also maintains a stable constant value with the error of observed direction increases.