3-D Acoustic Image Denoising for a Sonar System With Sparse Planar Arrays

Abstract

The development of three-dimensional (3-D) underwater imaging systems is restricted by the high hardware costs associated with the use of a large number of transducers, as well as poor image quality due to degrading noise. This report presents the design of a low-complexity 3-D underwater imaging system that can generate high-quality images. In particular, a complex-weight sparse synthesis method for a large planar array is presented to reduce the number of active elements. Then, a denoising network referred to as an asymmetric-pyramid globe residual network is proposed to enhance the acoustic images generated by the sparse planar arrays. This method can perceive the entirety of the 3-D acoustic images for denoising and effectively reduce the degradation effects due to speckle noise and sidelobes. The simulation results demonstrate that the resulting image quality is higher than that achieved using previously developed networks in terms of the peak signal-to-noise ratio and structural similarity index. To validate the proposed system further, an actual system based on the proposed methods was devised and tested via lake-based trials. The experimental results demonstrate the notable improvements obtained considering the sparsity rate and image quality relative to those presented in previous literature.