LAUSR

The development of real-time 3-D underwater imaging systems with large planar arrays involves high hardware costs and great computational burden. This study proposes the concept of fine-grid sparse arrays and the pruned distributed and parallel subarray (P-DPS) beamforming algorithm to achieve 3-D narrowband underwater imaging systems with low complexity. Fine-grid sparse arrays refine traditional half-wavelength grids to improve the freedom of the sparse optimization process and reduce the number of active elements. However, grid refinement increases the computational load of conventional fast beamforming algorithms. To solve this problem, a new pruned fast Fourier transform is proposed to eliminate all the redundant operations in the P-DPS beamforming, which is suitable for fine-grid sparse arrays. The computational load of the P-DPS beamforming seldom increases with grid refinement. The validity of the proposed method is verified with a fine-grid sparse planar array designed in the study. The computational load is then analyzed and compared with those of other methods. Results show the notable improvements in array sparsity rate and computational efficiency relative to those in the literature.