An improved histogram algorithm for DOA estimation based on single vector acoustic system

The integration of a singular vector acoustic system onto an unmanned underwater platform can lead to achieving unambiguous direction finding across the entire space. To enhance the direction-finding capabilities of the single vector acoustic system for low noise target, a refined histogram algorithm utilizing coherent spectrum weighting is suggested. A comparative evaluation and analysis of the target azimuth estimation performance of the enhanced histogram algorithm, traditional frequency-weighted histogram algorithm, and energy-weighted histogram algorithm are carried out. Through computer simulations, it is observed that the three Direction of Arrival (DOA) algorithms exhibit comparable direction-finding capabilities for wideband signals, whereas for single-frequency signals, the improved histogram algorithm surpasses the two conventional algorithms in direction-finding accuracy. Specifically, at a signal-to-noise ratio (SNR) of −40 dB, the azimuth estimation root mean square error (RMSE) is approximately 2°. Findings from sea trials indicate that the improved histogram algorithm displays a narrower spectral peak width and robust resistance to noise interference, thereby substantiating the effectiveness of the enhanced histogram algorithm.