Beamforming is one of the most important techniques for multibeam echo sounder (MBES) for engineering applications, such as seafloor topographic survey and underwater target detection. However, due to the Rayleigh limit in the conventional beamforming (CBF) algorithm, the output of the beamforming is often limited by the aperture and the number of elements, thus leading to low resolution and signal-to-noise ratio (SNR). To further improve the resolution and array gain (AG) of the beamforming algorithm for MBES, a dynamic background suppression deconvolved multiple signal classification (DBSD–MUSIC) algorithm is proposed in this work. The dynamic variable point scattering function (PSF) is constructed using the signal characteristics of the signal covariance matrix for each moment. The MUSIC azimuth spectrum is deconvolved using the dynamic PSF and Richardson–Lucy (R–L) iterative algorithm. Thus, the azimuth spectrum of DBSD–MUSIC algorithm is obtained. Based on the analysis and comparison of the simulation results and experimental multibeam data, we show that the resolution of the proposed algorithm is better than the traditional MUSIC algorithm. In addition, it also has a better AG and the direction of arrival (DOA) estimation performance.

波束赋形是多波束回声测深仪 (MBES) 在海底地形测量和水下目标探测等工程应用中最重要的技术之一。然而，由于传统波束形成（CBF）算法中的瑞利限制，波束形成的输出往往受到孔径和元件数量的限制，从而导致分辨率和信噪比（SNR）较低。为了进一步提高 MBES 波束形成算法的分辨率和阵列增益 (AG)，本文提出了一种动态背景抑制反卷积多信号分类 (DBSD-MUSIC) 算法。动态可变点散射函数 (PSF) 是利用每个时刻的信号协方差矩阵的信号特征构建的。使用动态 PSF 和 Richardson–Lucy (R–L) 迭代算法对 MUSIC 方位谱进行反卷积。这样就得到了DBSD-MUSIC算法的方位谱。通过对仿真结果和实验多波束数据的分析比较，表明所提算法的分辨率优于传统的MUSIC算法。此外，它还具有更好的AG和到达方向（DOA）估计性能。