High-resolution azimuth estimation algorithm based on data fusion for the vector hydrophone vertical array

To improve the performance of the high-resolution azimuth estimation for the vector hydrophone vertical array, the data fusion algorithm of the optimal weighted in the sub-band based on MUSIC was presented. The proposed algorithm first employ MUSIC technique to estimate the azimuth of each narrow band signal, and then the azimuth estimation results of multiple hydrophones are fusion processed by using the least square and optimal weighted methods. The final estimated result is achieved by adopting the weighted histogram statistics method. The results of the simulation and sea trials indicated that the proposed algorithm has better azimuth estimation performance than MUSIC algorithm of a single vector hydrophone and the data fusion technique based on the acoustic energy flux method. The better performance is reflected in the aspects of the estimation precision, the probability of correct estimation, the capability to distinguish multi-objects and the inhibition of the noise sub-bands.