Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar

Jie Huang,Tian Zhou,Jiajun Shen,Wanyuan Zhang,Weidong Du

doi:10.3390/s18114013

Abstract

A new fast deconvolved beamforming algorithm is proposed in this paper, and it can greatly reduce the computation complexity of the original Richardson–Lucy (R–L algorithm) deconvolution algorithm by utilizing the convolution theorem and the fast Fourier transform technique. This algorithm makes it possible for real-time high-resolution beamforming in a multibeam sonar system. This paper applies the new fast deconvolved beamforming algorithm to a high-frequency multibeam sonar system to obtain a high bearing resolution and low side lobe. In the sounding mode, it restrains the tunnel effect and makes the topographic survey more accurate. In the 2D acoustic image mode, it can obtain clear images, more details, and can better distinguish two close targets. Detailed implementation methods of the fast deconvolved beamforming are given, its computational complexity is analyzed, and its performance is evaluated with simulated and real data.

Highlights

Smart Ocean engineering systematically integrates a variety of marine sensors, including underwater acoustic sensors and underwater acoustic sensor networks [1,2,3,4], to develop and utilize a rich variety of resources
Multibeam sonar can provide the full sea depth, wide coverage, and high precision seabed topography, surficial seabed type information, and two-dimensional images of targets in the water column, all of which play an important role in the smart ocean, and the performance of multibeam sonar is seriously affected by the robust high-resolution beamforming algorithm
The advantage of conventional beamforming (CBF) is that it is robust and it can work in the condition of a low signal-to-noise ratio (SNR)

Summary

Introduction

Smart Ocean engineering systematically integrates a variety of marine sensors, including underwater acoustic sensors and underwater acoustic sensor networks [1,2,3,4], to develop and utilize a rich variety of resources. Multibeam sonar can provide the full sea depth, wide coverage, and high precision seabed topography, surficial seabed type information, and two-dimensional images of targets in the water column, all of which play an important role in the smart ocean, and the performance of multibeam sonar is seriously affected by the robust high-resolution beamforming algorithm. The advantage of CBF is that it is robust and it can work in the condition of a low signal-to-noise ratio (SNR). CBF suffers from fat beams and high-level side lobes, and it cannot detect a weak signal among loud interfering sources

Results

Discussion

Conclusion